36 Data Vault Jobs - Page 2

Type: Contract | Duration: 6 Months We are seeking an experienced Data Engineer to join our team for a 6-month contract assignment. The ideal candidate will work on data warehouse development, ETL pipelines, and analytics enablement using Snowflake, Azure Data Factory (ADF), dbt, and other tools. This role requires strong hands-on experience with data integration platforms, documentation, and pipeline optimizationespecially in cloud environments such as Azure and AWS. Key Responsibilities Build and maintain ETL pipelines using Fivetran, dbt, and Azure Data Factory Monitor and support production ETL jobs Develop and maintain data lineage documentation for all systems Design data mapping and documentation to aid QA/UAT testing Evaluate and recommend modern data integration tools Optimize shared data workflows and batch schedules Collaborate with Data Quality Analysts to ensure accuracy and integrity of data flows Participate in performance tuning and improvement recommendations Support BI/MDM initiatives including Data Vault and Data Lakes RequiredSkills 7+ years of experience in data engineering roles Strong command of SQL, with 5+ years of hands-on development Deep experience with Snowflake, Azure Data Factory, dbt Strong background with ETL tools (Informatica, Talend, ADF, dbt, etc.) Bachelor's in CS, Engineering, Math, or related field Experience in healthcare domain (working with PHI/PII data) Familiarity with scripting/programming (Python, Perl, Java, Linux-based environments) Excellent communication and documentation skills Experience with BI tools like Power BI, Cognos, etc. Organized, self-starter with strong time-management and critical thinking abilities Nice To Have Experience with Data Lakes and Data Vaults QA & UAT alignment with clear development documentation Multi-cloud experience (especially Azure, AWS)

Senior Data Engineer You are familiar with AWS and Azure Cloud. You have extensive knowledge of Snowflake , SnowPro Core certification is a must have. You have used DBT at least in one project to deploy models in production. You have configured and deployed Airflow and integrated various operator in airflow (especially DBT & Snowflake). You can design build, release pipelines and understand of Azure DevOps Ecosystem. You have excellent understanding of Python (especially PySpark) and able to write metadata driven programs. Familiar with Data Vault (Raw , Business) also concepts like Point In Time , Semantic Layer. You are resilient in ambiguous situations and can clearly articulate the problem in a business friendly way. You believe in documenting processes and managing the artifacts and evolving that over time.

Mandatory:- Data modelling ,SQL, Erwin or Er studio Data architect , Data Vault , Dimensional Modelling Work mode – Currently this is remote (WFH) but it’s not permanent WFH , once business ask the candidate to come to office, they must relocate. Required Candidate profile o Experience in Data vault 2.0 certification o Experience with data modeling tools such as SQLDBMS, ERwin, or similar. o Strong understanding of database management systems (DBMS) and SQL.

Key Responsibilities : Lead the design and development of scalable data pipelines using PySpark and ETL frameworks on Google Cloud Platform (GCP) . Own end-to-end data architecture and solutions, ensuring high availability, performance, and reliability. Collaborate with data scientists, analysts, and stakeholders to understand data needs and deliver actionable insights. Optimize complex SQL queries and support advanced data transformations. Ensure best practices in data governance, data quality, and security . Mentor junior engineers and contribute to team capability development. Requirements : 8+ years of experience in data engineering roles. Strong expertise in GCP data services (BigQuery, Dataflow, Pub/Sub, Composer, etc.). Hands-on experience with PySpark and building ETL pipelines at scale. Proficiency in SQL with the ability to write and optimize complex queries. Solid understanding of data modeling, warehousing, and performance tuning. Experience with CI/CD pipelines, version control, and infrastructure-as-code is a plus. Excellent problem-solving and communication skills. Preferred Qualifications : GCP Certification (e.g., Professional Data Engineer). Experience with Airflow, Kubernetes, or Terraform.

Dear Candidate, We are hiring a Data Engineer to build scalable data pipelines and infrastructure to power analytics and machine learning. Ideal for those passionate about data integrity, automation, and performance. Key Responsibilities: Design ETL/ELT pipelines using tools like Airflow or dbt Build data lakes and warehouses (BigQuery, Redshift, Snowflake) Automate data quality checks and monitoring Collaborate with analysts, data scientists, and backend teams Optimize data flows for performance and cost Required Skills & Qualifications: Proficiency in SQL, Python, and distributed systems (e.g., Spark) Experience with cloud data platforms (AWS, GCP, or Azure) Strong understanding of data modeling and warehousing principles Bonus: Experience with Kafka, Parquet/Avro, or real-time streaming Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

Warm Greetings from SP Staffing Services Private Limited!! We have an urgent opening with our CMMI Level5 client for the below position. Please send your update profile if you are interested. Relevant Experience: 8 - 15 Yrs Location: Pan India Job Description: Minimum Two years experience in Boomi Data modeling Interested can share your resume to sankarspstaffings@gmail.com with below inline details. Over All Exp : Relevant Exp : Current CTC : Expected CTC : Notice Period :

Project Role : Application Support Engineer Project Role Description : Act as software detectives, provide a dynamic service identifying and solving issues within multiple components of critical business systems. Must have skills : Cloud Data Architecture Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Data ArchitectKemper is seeking a Data Architect to join our team. You will work as part of a distributed team and with Infrastructure, Enterprise Data Services and Application Development teams to coordinate the creation, enrichment, and movement of data throughout the enterprise. Your central responsibility as an architect will be improving the consistency, timeliness, quality, security, and delivery of data as part of Kemper's Data Governance framework. In addition, the Architect must streamline data flows and optimize cost management in a hybrid cloud environment. Your duties may include assessing architectural models and supervising data migrations across IaaS, PaaS, SaaS and on premises systems, as well as data platform selection and, on-boarding of data management solutions that meet the technical and operational needs of the company. To succeed in this role, you should know how to examine new and legacy requirements and define cost effective patterns to be implemented by other teams. You must then be able to represent required patterns during implementation projects. The ideal candidate will have proven experience in cloud (Snowflake, AWS and Azure) architectural analysis and management. Responsibilities Define architectural standards and guidelines for data products and processes. Assess and document when and how to use existing and newly architected producers and consumers, the technologies to be used for various purposes, and models of selected entities and processes. The guidelines should encourage reuse of existing data products, as well as address issues of security, timeliness, and quality. Work with Information & Insights, Data Governance, Business Data Stewards, and Implementation teams to define standard and ad-hoc data products and data product sets. Work with Enterprise Architecture, Security, and Implementation teams to define the transformation of data products throughout hybrid cloud environments assuring that both functional and non-functional requirements are addressed. This includes the ownership, frequency of movement, the source and destination of each step, how the data is transformed as it moves, and any aggregation or calculations. Working with Data Governance and project teams to model and map data sources, including descriptions of the business meaning of the data, its uses, its quality, the applications that maintain it and the technologies in which it is stored. Documentation of a data source must describe the semantics of the data so that the occasional subtle differences in meaning are understood. Defining integrative views of data to draw together data from across the enterprise. Some views will use data stores of extracted data and others will bring together data in near real time. Solutions must consider data currency, availability, response times and data volumes, etc. Working with modeling and storage teams to define Conceptual, Logical and Physical data views limiting technical debt as data flows through transformations. Investigating and leading participation in POCs of emerging technologies and practices. Leveraging and evolving existing [core] data products and patterns. Communicate and lead understanding of data architectural services across the enterprise. Ensure a focus on data quality by working effectively with data and system stewards. QualificationsBachelor's degree in computer science, Computer Engineering, or equivalent experience. A minimum of 3 years' experience in a similar role. Demonstrable knowledge of Secure DevOps and SDLC processes. Must have AWS or Azure experience.Experience with Data Vault 2 required. Snowflake a plus.Familiarity of system concepts and tools within an enterprise architecture framework. Including Cataloging, MDM, RDM, Data Lakes, Storage Patterns, etc. Excellent organizational and analytical abilities. Outstanding problem solver. Good written and verbal communication skills.

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Modeling Techniques and Methodologies Good to have skills : Data Engineering, Cloud Data Migration Minimum 9 year(s) of experience is required Educational Qualification : BE or BTech must Project Role :Data Platform Engineer Project Role Description :Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have Skills :Data Modeling Techniques and Methodologies, SSI: NON SSI:Good to Have Skills :SSI:Data Engineering, Cloud Data Migration NON SSI :Job Requirements :Key Responsibilities :1Drive discussions with clients deal teams to understand business requirements, how Industry Data Model fits in implementation and solutioning 2Develop the solution blueprint and scoping, estimation, staffing for delivery project and solutioning 3Drive Discovery activities and design workshops with client and lead strategic road mapping and operating model design discussions 4Good to have Data Vault,Cloud DB design,Graph data modeling, Ontology, Data Engineering,Data Lake design Technical Experience :1 9plus year overall exp,4plus Data Modeling,Cloud DB Model,3NF,Dimensional,Conversion of RDBMS data model to Graph Data ModelInstrumental in DB design through all stages of Data Model 2 Exp on at least one Cloud DB Design work must be familiar with Data Architecture Principles Professional Attributes :1Strong requirement analysis and technical solutioning skill in Data and Analytics 2Excellent writing, communication and presentation skills 3Eagerness to learn and develop self on an ongoing basis 4Excellent client facing and interpersonal skills Educational Qualification:BE or BTech mustAdditional Info :Exp in estimation,PoVs,Solution Approach creation Exp on data transformation,analytic projects,DWH Qualification BE or BTech must

Project Role : Application Support Engineer Project Role Description : Act as software detectives, provide a dynamic service identifying and solving issues within multiple components of critical business systems. Must have skills : Cloud Data Architecture Good to have skills : Cloud Infrastructure Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Data ArchitectKemper is seeking a Data Architect to join our team. You will work as part of a distributed team and with Infrastructure, Enterprise Data Services and Application Development teams to coordinate the creation, enrichment, and movement of data throughout the enterprise. Your central responsibility as an architect will be improving the consistency, timeliness, quality, security, and delivery of data as part of Kemper's Data Governance framework. In addition, the Architect must streamline data flows and optimize cost management in a hybrid cloud environment. Your duties may include assessing architectural models and supervising data migrations across IaaS, PaaS, SaaS and on premises systems, as well as data platform selection and, on-boarding of data management solutions that meet the technical and operational needs of the company. To succeed in this role, you should know how to examine new and legacy requirements and define cost effective patterns to be implemented by other teams. You must then be able to represent required patterns during implementation projects. The ideal candidate will have proven experience in cloud (Snowflake, AWS and Azure) architectural analysis and management. Responsibilities Define architectural standards and guidelines for data products and processes. Assess and document when and how to use existing and newly architected producers and consumers, the technologies to be used for various purposes, and models of selected entities and processes. The guidelines should encourage reuse of existing data products, as well as address issues of security, timeliness, and quality. Work with Information & Insights, Data Governance, Business Data Stewards, and Implementation teams to define standard and ad-hoc data products and data product sets. Work with Enterprise Architecture, Security, and Implementation teams to define the transformation of data products throughout hybrid cloud environments assuring that both functional and non-functional requirements are addressed. This includes the ownership, frequency of movement, the source and destination of each step, how the data is transformed as it moves, and any aggregation or calculations. Working with Data Governance and project teams to model and map data sources, including descriptions of the business meaning of the data, its uses, its quality, the applications that maintain it and the technologies in which it is stored. Documentation of a data source must describe the semantics of the data so that the occasional subtle differences in meaning are understood. Defining integrative views of data to draw together data from across the enterprise. Some views will use data stores of extracted data and others will bring together data in near real time. Solutions must consider data currency, availability, response times and data volumes, etc. Working with modeling and storage teams to define Conceptual, Logical and Physical data views limiting technical debt as data flows through transformations. Investigating and leading participation in POCs of emerging technologies and practices. Leveraging and evolving existing [core] data products and patterns. Communicate and lead understanding of data architectural services across the enterprise. Ensure a focus on data quality by working effectively with data and system stewards. QualificationsBachelor's degree in computer science, Computer Engineering, or equivalent experience. A minimum of 3 years' experience in a similar role. Demonstrable knowledge of Secure DevOps and SDLC processes. Must have AWS or Azure experience.Experience with Data Vault 2 required. Snowflake a plus.Familiarity of system concepts and tools within an enterprise architecture framework. Including Cataloging, MDM, RDM, Data Lakes, Storage Patterns, etc. Excellent organizational and analytical abilities. Outstanding problem solver. Good written and verbal communication skills.

Role & responsibilities: Experience: 6+ years of experience in data analysis, with at least 2+ years of experience in DataVault modeling. Prior experience in the financial services domain is highly preferred. Technical Skills: Strong proficiency in SQL and hands-on experience with DataVault 2.0 methodology. Familiarity with data analysis tools like Python, R, or SAS. Experience with ETL/ELT tools and cloud data platforms (e.g., Azure Synapse, AWS Redshift, or GCP BigQuery). Knowledge of Wherescape 3D and RED for modelling DataVault Data Visualization: Proficiency in creating dashboards and reports using tools such as Power BI, Tableau, or Qlik. Soft Skills: Excellent analytical thinking and problem-solving abilities. Strong communication skills to effectively collaborate with technical and non-technical stakeholders. Knowledge of Financial Services: Understanding of key financial metrics and regulatory requirements, such as Basel III or SOX compliance.

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Data Modeling Techniques and Methodologies Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have Skills : Data Modeling Techniques and Methodologies, SSI: NON SSI: Good to Have Skills :SSI: Data Engineering, Cloud Data Migration NON SSI : Job Requirements : Key Responsibilities : 1Drive discussions with clients deal teams to understand business requirements, how Industry Data Model fits in implementation and solutioning 2Develop the solution blueprint and scoping, estimation, staffing for delivery project and solutioning 3Drive Discovery activities and design workshops with client and lead strategic road mapping and operating model design discussions 4Good to have Data Vault,Cloud DB design,Graph data modeling, Ontology, Data Engineering,Data Lake design Technical Experience : 1 7plus year overall exp,3plus Data Modeling,Cloud DB Model,3NF,Dimensional,Conversion of RDBMS data model to Graph Data ModelInstrumental in DB design through all stages of Data Model 2 Exp on at least one Cloud DB Design work must be familiar with Data Architecture Principles Professional Attributes : 1Strong requirement analysis and technical solutioning skill in Data and Analytics 2Excellent writing, communication and presentation skills 3Eagerness to learn and develop self on an ongoing basis 4Excellent client facing and interpersonal skills