142 Cloudera Jobs - Page 2

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform. Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation. Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Non-Degree Program Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms. Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

In one sentence We are seeking an experienced Kafka Administrator to manage and maintain our Apache Kafka infrastructure, with a strong focus on deployments within OpenShift and Cloudera environments. The ideal candidate will have hands-on experience with Kafka clusters, container orchestration, and big data platforms, ensuring high availability, performance, and security. What will your job look like? Install, configure, and manage Kafka clusters in production and non-production environments. Deploy and manage Kafka on OpenShift using Confluent for Kubernetes (CFK) or similar tools. Integrate Kafka with Cloudera Data Platform (CDP), including services like NiFi, HBase, and Solr. Monitor Kafka performance and implement tuning strategies for optimal throughput and latency. Implement and manage Kafka security using SASL_SSL, Kerberos, and RBAC. Perform upgrades, patching, and backup/recovery of Kafka environments. Collaborate with DevOps and development teams to support CI/CD pipelines and application integration. Troubleshoot and resolve Kafka-related issues in a timely manner. Maintain documentation and provide knowledge transfer to team members. All you need is... 5+ years of experience as a Kafka Administrator. 2+ years of experience deploying Kafka on OpenShift or Kubernetes. Strong experience with Cloudera ecosystem and integration with Kafka. Proficiency in Kafka security protocols (SASL_SSL, Kerberos). Experience with monitoring tools like Prometheus, Grafana, or Confluent Control Center. Solid understanding of Linux systems and shell scripting. Familiarity with CI/CD tools (Jenkins, GitLab CI, etc.). Excellent problem-solving and communication skills.

Interview Mode: Virtual (2 Rounds) Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark , Python , and working with modern data engineering tools in cloud environments such as AWS . Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments Skills: ci/cd,zeppelin,pycharm,pyspark,etl tools,control-m,unit test cases,tableau,performance tuning,jenkins,qlikview,informatica,jupyter notebook,api integration,unix/linux,git,aws s3,hive,cloudera,jasper,airflow,cdc,pyspark, apache spark, python, aws s3, airflow/control-m, sql, unix/linux, hive, hadoop, data modeling, and performance tuning,agile methodologies,aws,s3,data modeling,data validation,ai/ml model development,batch integration,apache spark,python,etl pipelines,shell scripting,hortonworks,real-time integration,hadoop

Interview Mode: Virtual (2 Rounds) Type: Contract-to-Hire (C2H) Job Summary We are looking for a skilled PySpark Developer with hands-on experience in building scalable data pipelines and processing large datasets. The ideal candidate will have deep expertise in Apache Spark , Python , and working with modern data engineering tools in cloud environments such as AWS . Key Skills & Responsibilities Strong expertise in PySpark and Apache Spark for batch and real-time data processing. Experience in designing and implementing ETL pipelines, including data ingestion, transformation, and validation. Proficiency in Python for scripting, automation, and building reusable components. Hands-on experience with scheduling tools like Airflow or Control-M to orchestrate workflows. Familiarity with AWS ecosystem, especially S3 and related file system operations. Strong understanding of Unix/Linux environments and Shell scripting. Experience with Hadoop, Hive, and platforms like Cloudera or Hortonworks. Ability to handle CDC (Change Data Capture) operations on large datasets. Experience in performance tuning, optimizing Spark jobs, and troubleshooting. Strong knowledge of data modeling, data validation, and writing unit test cases. Exposure to real-time and batch integration with downstream/upstream systems. Working knowledge of Jupyter Notebook, Zeppelin, or PyCharm for development and debugging. Understanding of Agile methodologies, with experience in CI/CD tools (e.g., Jenkins, Git). Preferred Skills Experience in building or integrating APIs for data provisioning. Exposure to ETL or reporting tools such as Informatica, Tableau, Jasper, or QlikView. Familiarity with AI/ML model development using PySpark in cloud environments Skills: ci/cd,zeppelin,pycharm,pyspark,etl tools,control-m,unit test cases,tableau,performance tuning,jenkins,qlikview,informatica,jupyter notebook,api integration,unix/linux,git,aws s3,hive,cloudera,jasper,airflow,cdc,pyspark, apache spark, python, aws s3, airflow/control-m, sql, unix/linux, hive, hadoop, data modeling, and performance tuning,agile methodologies,aws,s3,data modeling,data validation,ai/ml model development,batch integration,apache spark,python,etl pipelines,shell scripting,hortonworks,real-time integration,hadoop

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Candidates must have experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems 10 - 15 years of experience in data engineering and architecting data platforms 5 – 8 years’ experience in architecting and implementing Data Platforms Azure Cloud Platform. 5 – 8 years’ experience in architecting and implementing Data Platforms on-prem (Hadoop or DW appliance) Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow. Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc Candidates should have experience in delivering both business decision support systems (reporting, analytics) and data science domains / use cases

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

A Data Engineer specializing in enterprise data platforms, experienced in building, managing, and optimizing data pipelines for large-scale environments. Having expertise in big data technologies, distributed computing, data ingestion, and transformation frameworks. Proficient in Apache Spark, PySpark, Kafka, and Iceberg tables, and understand how to design and implement scalable, high-performance data processing solutions.What you’ll doAs a Data Engineer – Data Platform Services, responsibilities include: Data Ingestion & Processing Designing and developing data pipelines to migrate workloads from IIAS to Cloudera Data Lake. Implementing streaming and batch data ingestion frameworks using Kafka, Apache Spark (PySpark). Working with IBM CDC and Universal Data Mover to manage data replication and movement. Big Data & Data Lakehouse Management Implementing Apache Iceberg tables for efficient data storage and retrieval. Managing distributed data processing with Cloudera Data Platform (CDP). Ensuring data lineage, cataloging, and governance for compliance with Bank/regulatory policies. Optimization & Performance Tuning Optimizing Spark and PySpark jobs for performance and scalability. Implementing data partitioning, indexing, and caching to enhance query performance. Monitoring and troubleshooting pipeline failures and performance bottlenecks. Security & Compliance Ensuring secure data access, encryption, and masking using Thales CipherTrust. Implementing role-based access controls (RBAC) and data governance policies. Supporting metadata management and data quality initiatives. Collaboration & Automation Working closely with Data Scientists, Analysts, and DevOps teams to integrate data solutions. Automating data workflows using Airflow and implementing CI/CD pipelines with GitLab and Sonatype Nexus. Supporting Denodo-based data virtualization for seamless data access Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 4-7 years of experience in big data engineering, data integration, and distributed computing. Strong skills in Apache Spark, PySpark, Kafka, SQL, and Cloudera Data Platform (CDP). Proficiency in Python or Scala for data processing. Experience with data pipeline orchestration tools (Apache Airflow, Stonebranch UDM). Understanding of data security, encryption, and compliance frameworks Preferred technical and professional experience Experience in banking or financial services data platforms. Exposure to Denodo for data virtualization and DGraph for graph-based insights. Familiarity with cloud data platforms (AWS, Azure, GCP). Certifications in Cloudera Data Engineering, IBM Data Engineering, or AWS Data Analytics

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations. Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala ; Minimum 3 years of experience on Cloud Data Platforms on AWS; Experience in AWS EMR / AWS Glue / Data Bricks, AWS RedShift, DynamoDB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers

As a senior SAP Consultant, you will serve as a client-facing practitioner working collaboratively with clients to deliver high-quality solutions and be a trusted business advisor with deep understanding of SAP Accelerate delivery methodology or equivalent and associated work products. You will work on projects that assist clients in integrating strategy, process, technology, and information to enhance effectiveness, reduce costs, and improve profit and shareholder value. There are opportunities for you to acquire new skills, work across different disciplines, take on new challenges, and develop a comprehensive understanding of various industries. Your primary responsibilities include: Strategic SAP Solution FocusWorking across technical design, development, and implementation of SAP solutions for simplicity, amplification, and maintainability that meet client needs. Comprehensive Solution DeliveryInvolvement in strategy development and solution implementation, leveraging your knowledge of SAP and working with the latest technologies. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies. Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers

As a senior SAP Consultant, you will serve as a client-facing practitioner working collaboratively with clients to deliver high-quality solutions and be a trusted business advisor with deep understanding of SAP Accelerate delivery methodology or equivalent and associated work products. You will work on projects that assist clients in integrating strategy, process, technology, and information to enhance effectiveness, reduce costs, and improve profit and shareholder value. There are opportunities for you to acquire new skills, work across different disciplines, take on new challenges, and develop a comprehensive understanding of various industries. Your primary responsibilities include: Strategic SAP Solution FocusWorking across technical design, development, and implementation of SAP solutions for simplicity, amplification, and maintainability that meet client needs. Comprehensive Solution DeliveryInvolvement in strategy development and solution implementation, leveraging your knowledge of SAP and working with the latest technologies. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala. Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies. Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB Good to excellent SQL skills Preferred technical and professional experience Certification in AWS and Data Bricks or Cloudera Spark Certified developers

Practice Overview: Skill/Operating Group Technology Consulting Level Consultant Location Gurgaon / Mumbai / Bangalore / Kolkata / Pune Travel Percentage Expected Travel could be anywhere between 0-100% Principal Duties And Responsibilities: Working closely with our clients, Consulting professionals design, build and implement strategies that can help enhance business performance. They develop specialized expertisestrategic, industry, functional, technicalin a diverse project environment that offers multiple opportunities for career growth. The opportunities to make a difference within exciting client initiatives are limitless in this ever-changing business landscape. Here are just a few of your day-to-day responsibilities. Architect large scale data lake, DW, and Delta Lake on cloud solutions using AWS, Azure, GCP, Ali Cloud, Snowflake, Hadoop, or Cloudera Design Data Mesh Strategy and Architecture Build strategy and roadmap for data migration to cloud Establish Data Governance Strategy & Operating Model Implementing programs/interventions that prepare the organization for implementation of new business processes Deep understanding of Data and Analytics platforms, data integration w/ cloud Provide thought leadership to the downstream teams for developing offerings and assets Identifying, assessing, and solvingcomplex business problemsfor area of responsibility, where analysis of situations or data requires an in-depth evaluation of variable factors Overseeing the production and implementation of solutions covering multiple cloud technologies, associated Infrastructure / application architecture, development, and operating models Called upon to apply your solid understanding of Data, Data on cloud and disruptive technologies. Driving enterprise business, application, and integration architecture Helping solve key business problems and challenges by enabling a cloud-based architecture transformation, painting a picture of, and charting a journey from the current state to a to-be enterprise environment Assisting our clients to build the required capabilities for growth and innovation to sustain high performance Managing multi-disciplinary teams to shape, sell, communicate, and implement programs Experience in participating in client presentations & orals for proposal defense etc. Experience in effectively communicating the target state, architecture & topology on cloud to clients Qualifications: Bachelors degree MBA Degree from Tier-1 College (Preferable) 6-10 years of large-scale consulting experience and/or working with hi tech companies in data architecture, data governance, data mesh, data security and management. Certified on DAMA (Data Management) or Azure Data Architecture or Google Cloud Data Analytics or AWS Data Analytics Experience: We are looking for experienced professionals with Data strategy, data architecture, data on cloud, data modernization, data operating model and data security experience across all stages of the innovation spectrum, with a remit to build the future in real-time. The candidate should have practical industry expertise in one of these areas - Financial Services, Retail, consumer goods, Telecommunications, Life Sciences, Transportation, Hospitality, Automotive/Industrial, Mining and Resources. Key Competencies and Skills: The right candidate should have competency and skills aligned to one or more of these archetypes - Data SME - Experience in deal shaping & strong presentation skills, leading proposal experience, customer orals; technical understanding of data platforms, data on cloud strategy, data strategy, data operating model, change management of data transformation programs, data modeling skills. Data on Cloud Architect - Technical understanding of data platform strategy for data on cloud migrations, big data technologies, experience in architecting large scale data lake and DW on cloud solutions. Experience one or more technologies in this space:AWS, Azure, GCP, AliCloud, Snowflake, Hadoop, Cloudera Data Strategy - Data Capability Maturity Assessment, Data & Analytics / AI Strategy, Data Operating Model & Governance, Data Hub Enablement, Data on Cloud Strategy, Data Architecture Strategy Data Transformation Lead - Understanding of data supply chain and data platforms on cloud, experience in conducting alignment workshops, building value realization framework for data transformations, program management experience Exceptional interpersonal and presentation skills - ability to convey technology and business value propositions to senior stakeholders Capacity to develop high impact thought leadership that articulates a forward-thinking view of the market Other desired skills - Strong desire to work in technology-driven business transformation Strong knowledge of technology trends across IT and digital and how they can be applied to companies to address real world problems and opportunities. Comfort conveying both high-level and detailed information, adjusting the way ideas are presented to better address varying social styles and audiences. Leading proof of concept and/or pilot implementations and defining the plan to scale implementations across multiple technology domains Flexibility to accommodate client travel requirements Published Thought leadership Whitepapers, POVs

Data Strategy & Data Governance Manager Join our team in Technology Strategy for an exciting career opportunity to enable our most strategic clients to realize exceptional business value from technology Practice: Technology Strategy & Advisory, Capability Network Areas of Work: Data Strategy Level: Manager | Location: Bangalore / Gurgaon / Mumbai / Pune / Chennai / Hyderabad / Kolkata | Years of Exp: 10 to 15 years Explore an Exciting Career at Accenture Do you believe in creating an impactAre you a problem solver who enjoys working on transformative strategies for global clientsAre you passionate about being part of an inclusive, diverse and collaborative culture Then, this is the right place for you! Welcome to a host of exciting global opportunities in Accenture Technology Strategy & Advisory. The Practice- A Brief Sketch: The Technology Strategy & Advisory Practice is a part of and focuses on the clients most strategic priorities. We help clients achieve growth and efficiency through innovative R&D transformation, aimed at redefining business models using agile methodologies. As part of this high performing team, you will work on the scaling Data & Analyticsand the data that fuels it allto power every single person and every single process. You will part of our global team of experts who work on the right scalable solutions and services that help clients achieve your business objectives faster. Business Transformation: Assessment of Data & Analytics potential and development of use cases that can transform business Transforming Businesses: Envisioning and Designing customized, next-generation data and analytics products and services that help clients shift to new business models designed for today's connectedlandscape of disruptive technologies Formulation of Guiding Principles and Components: Assessing impact to clients technology landscape/ architecture and ensuring formulation of relevant guiding principles and platform components. Product and Frameworks :Evaluate existing data and analytics products and frameworks available and develop options for proposed solutions. Bring your best skills forward to excel in the role: Leverage your knowledge of technology trends across Data & Analytics and how they can be applied to address real world problems and opportunities. Interact with client stakeholders to understand their Data & Analytics problems, priority use-cases, define a problem statement, understand the scope of the engagement, and also drive projects to deliver value to the client Design & guide development of Enterprise-wide Data & Analytics strategy for our clients that includes Data & Analytics Architecture, Data on Cloud, Data Quality, Metadata and Master Data strategy Establish framework for effective Data Governance across multispeed implementations. Define data ownership, standards, policies and associated processes Define a Data & Analytics operating model to manage data across organization . Establish processes around effective data management ensuring Data Quality & Governance standards as well as roles for Data Stewards Benchmark against global research benchmarks and leading industry peers to understand current & recommend Data & Analytics solutions Conduct discovery workshops and design sessions to elicit Data & Analytics opportunities and client pain areas. Develop and Drive Data Capability Maturity Assessment, Data & Analytics Operating Model & Data Governance exercises for clients A fair understanding of data platform strategy for data on cloud migrations, big data technologies, large scale data lake and DW on cloud solutions. Utilize strong expertise & certification in any of the Data & Analytics on Cloud platforms Google, Azure or AWS Collaborate with business experts for business understanding, working with other consultants and platform engineers for solutions and with technology teams for prototyping and client implementations. Create expert content and use advanced presentation, public speaking, content creation and communication skills for C-Level discussions. Demonstrate strong understanding of a specific industry , client or technology and function as an expert to advise senior leadership. Manage budgeting and forecasting activities and build financial proposals Qualification Your experience counts! MBA from a tier 1 institute 5 7 years of Strategy Consulting experience at a consulting firm 3+ years of experience on projects showcasing skills across these capabilities- Data Capability Maturity Assessment, Data & Analytics Strategy, Data Operating Model & Governance, Data on Cloud Strategy, Data Architecture Strategy At least 2 years of experience on architecting or designing solutions for any two of these domains - Data Quality, Master Data (MDM), Metadata, data lineage, data catalog. Experience in one or more technologies in the data governance space:Collibra, Talend, Informatica, SAP MDG, Stibo, Alteryx, Alation etc. 3+ years of experience in designing end-to-end Enterprise Data & Analytics Strategic Solutions leveraging Cloud & Non-Cloud platforms like AWS, Azure, GCP, AliCloud, Snowflake, Hadoop, Cloudera, Informatica, Snowflake, Palantir Deep Understanding of data supply chain and building value realization framework for data transformations 3+ years of experience leading or managing teams effectively including planning/structuring analytical work, facilitating team workshops, and developing Data & Analytics strategy recommendations as well as developing POCs Foundational understanding of data privacy is desired Mandatory knowledge of IT & Enterprise architecture concepts through practical experience and knowledge of technology trends e.g. Mobility, Cloud, Digital, Collaboration A strong understanding in any of the following industries is preferred:Financial Services, Retail, Consumer Goods, Telecommunications, Life Sciences, Transportation, Hospitality, Automotive/Industrial, Mining and Resources or equivalent domains CDMP Certification from DAMA preferred Cloud Data & AI Practitioner Certifications (Azure, AWS, Google) desirable but not essential

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Must have 5+ years exp in Big Data -Hadoop Spark -Scala ,Python Hbase, Hive Good to have Aws -S3, athena ,Dynomo DB, Lambda, Jenkins GIT Developed Python and pyspark programs for data analysis. Good working experience with python to develop Custom Framework for generating of rules (just like rules engine). Developed Python code to gather the data from HBase and designs the solution to implement using Pyspark. Apache Spark DataFrames/RDD's were used to apply business transformations and utilized Hive Context objects to perform read/write operations Preferred technical and professional experience Understanding of Devops. Experience in building scalable end-to-end data ingestion and processing solutions Experience with object-oriented and/or functional programming languages, such as Python, Java and Scala

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and Azure Cloud Data Platform Responsibilities: Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform or HDFS Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform Experience in developing streaming pipelines Experience to work with Hadoop / Azure eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala; Minimum 3 years of experience on Cloud Data Platforms on Azure; Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB Good to excellent SQL skills Exposure to streaming solutions and message brokers like Kafka technologies Preferred technical and professional experience Certification in Azure and Data Bricks or Cloudera Spark Certified developers

Develop, test, and deploy data processing applications using Apache Spark and Scala. Optimize and tune Spark applications for better performance on large-scale data sets. Work with the Cloudera Hadoop ecosystem (e.g., HDFS, Hive, Impala, HBase, Kafka) to build data pipelines and storage solutions. Collaborate with data scientists, business analysts, and other developers to understand data requirements and deliver solutions. Design and implement high-performance data processing and analytics solutions. Ensure data integrity, accuracy, and security across all processing tasks. Troubleshoot and resolve performance issues in Spark, Cloudera, and related technologies. Implement version control and CI/CD pipelines for Spark applications. Required Skills & Experience: Minimum 8 years of experience in application development. Strong hands on experience in Apache Spark, Scala, and Spark SQL for distributed data processing. Hands-on experience with Cloudera Hadoop (CDH) components such as HDFS, Hive, Impala, HBase, Kafka, and Sqoop. Familiarity with other Big Data technologies, including Apache Kafka, Flume, Oozie, and Nifi. Experience building and optimizing ETL pipelines using Spark and working with structured and unstructured data. Experience with SQL and NoSQL databases such as HBase, Hive, and PostgreSQL. Knowledge of data warehousing concepts, dimensional modeling, and data lakes. Ability to troubleshoot and optimize Spark and Cloudera platform performance. Familiarity with version control tools like Git and CI/CD tools (e.g., Jenkins, GitLab).

Project Role : Application Developer Project Role Description : Design, build and configure applications to meet business process and application requirements. Must have skills : Informatica PowerCenter Good to have skills : Oracle Applications Development, ControlM AdministrationMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Application Support Engineer, you will support multiple applications in Acceptance to meet business process and application requirements. Roles & Responsibilities:- Support Batch runs and provide solution in case of failures in Acceptance- Deployment of the code in acceptance environments.- Collaborate with different application teams and resolve batch/deployment issues if any- Provide services during acceptance test batch run, as agreed between the Engagement Managers at a later point in time.- Acceptance support to handle the issues if any post deployment.- Expected to be an SME, collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Implement and maintain data pipelines.- Provide System documentation. Professional & Technical Skills: - Must Have Skills: Proficiency in Control M, Informatica PowerCenter, SQL- Strong understanding of database concepts.- Experience with SQL, relational databases, HDFS, Yarn- Must have experience working on Control M-Good to have Cloudera Manager experience- Knowledge of data warehousing concepts. Additional Information:- The candidate should have a minimum of 5 years of experience in Control M, Informatica PowerCenter- A 15 year full-time education is required Qualification 15 years full time education

Skill : Java, Spark, Kafka Experience : 10 to 16 years Location : Hyderabad As Data Engineer, you will : Support in designing and rolling out the data architecture and infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources Identify data source, design and implement data schema/models and integrate data that meet the requirements of the business stakeholders Play an active role in the end-to-end delivery of AI solutions, from ideation, feasibility assessment, to data preparation and industrialization. Work with business, IT and data stakeholders to support with data-related technical issues, their data infrastructure needs as well as to build the most flexible and scalable data platform. With a strong focus on DataOps, design, develop and deploy scalable batch and/or real-time data pipelines. Design, document, test and deploy ETL/ELT processes Find the right tradeoffs between the performance, reliability, scalability, and cost of the data pipelines you implement Monitor data processing efficiency and propose solutions for improvements. • Have the discipline to create and maintain comprehensive project documentation. • Build and share knowledge with colleagues and coach junior profiles.

job requisition idJR1027452 Overall Responsibilities: Data Pipeline Development: Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy. Data Ingestion: Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP. Data Transformation and Processing: Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements. Performance Optimization: Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes. Data Quality and Validation: Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline. Automation and Orchestration: Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem. Monitoring and Maintenance: Monitor pipeline performance, troubleshoot issues, and perform routine maintenance on the Cloudera Data Platform and associated data processes. Collaboration: Work closely with other data engineers, analysts, product managers, and other stakeholders to understand data requirements and support various data-driven initiatives. Documentation: Maintain thorough documentation of data engineering processes, code, and pipeline configurations. Software : Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques. Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase. Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala). Familiarity with Hadoop, Kafka, and other distributed computing tools. Experience with Apache Oozie, Airflow, or similar orchestration frameworks. Strong scripting skills in Linux. Category-wise Technical Skills: PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques. Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase. Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala). Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools. Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks. Scripting and Automation: Strong scripting skills in Linux. Experience: 5-12 years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform. Proven track record of implementing data engineering best practices. Experience in data ingestion, transformation, and optimization on the Cloudera Data Platform. Day-to-Day Activities: Design, develop, and maintain ETL pipelines using PySpark on CDP. Implement and manage data ingestion processes from various sources. Process, cleanse, and transform large datasets using PySpark. Conduct performance tuning and optimization of ETL processes. Implement data quality checks and validation routines. Automate data workflows using orchestration tools. Monitor pipeline performance and troubleshoot issues. Collaborate with team members to understand data requirements. Maintain documentation of data engineering processes and configurations. Qualifications: Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. Relevant certifications in PySpark and Cloudera technologies are a plus. Soft Skills: Strong analytical and problem-solving skills. Excellent verbal and written communication abilities. Ability to work independently and collaboratively in a team environment. Attention to detail and commitment to data quality.

Managing Sales of Loan Against Property & Business Loans for the Ameerpet Region. Lead a team of Relationship Managers to generate business through Direct sourcing. Building the Sales and distribution network in the assigned territory. Recruit, train and monitor team members & ensuring quality service delivery. Managing loan process from lead generation till disbursement of the loan. Ensure synergy between sales, credit and operation to ensure the efficiency of business processes

Req ID: 324609 We are currently seeking a Data Engineer to join our team in Pune, Mahrshtra (IN-MH), India (IN). Key Responsibilities: Design and implement tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack. Provide thought leadership by recommending the most appropriate technologies and solutions for a given use case, covering the entire spectrum from the application layer to infrastructure. Demonstrate proficiency in coding skills, utilizing languages such as Python, Java, and Scala to efficiently move solutions into production while prioritizing performance, security, scalability, and robust data integrations. Collaborate seamlessly across diverse technical stacks, including Cloudera, Databricks, Snowflake, and AWS. Develop and deliver detailed presentations to effectively communicate complex technical concepts. Generate comprehensive solution documentation, including sequence diagrams, class hierarchies, logical system views, etc. Adhere to Agile practices throughout the solution development process. Design, build, and deploy databases and data stores to support organizational requirements. Basic Qualifications: 4+ years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects. 2+ years of experience leading a team supporting data related projects to develop end-to-end technical solutions. Experience with Informatica, Python, Databricks, Azure Data Engineer Ability to travel at least 25%." Preferred Skills: Demonstrate production experience in core data platforms such as Snowflake, Databricks, AWS, Azure, GCP, Hadoop, and more. Possess hands-on knowledge of Cloud and Distributed Data Storage, including expertise in HDFS, S3, ADLS, GCS, Kudu, ElasticSearch/Solr, Cassandra, or other NoSQL storage systems. Exhibit a strong understanding of Data integration technologies, encompassing Informatica, Spark, Kafka, eventing/streaming, Streamsets, NiFi, AWS Data Migration Services, Azure DataFactory, Google DataProc. Showcase professional written and verbal communication skills to effectively convey complex technical concepts. Undergraduate or Graduate degree preferred