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PwC Service Delivery Center
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IN_Senior Associate_ Azure DE__Data and Analytics_Advisory_Remote&Hyd

IN_Senior Associate_ Azure DE__Data and Analytics_Advisory_Remote&Hyd

PwC Service Delivery Center

4 - 7 years

9 - 13 Lacs

Hyderabad

Posted:1 week ago| Platform:

Apply

Skills Required

Computer science Data modeling Postgresql MySQL Database administration Agile DBMS Apache Monitoring Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

& Summary

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decisionmaking and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Why PWC

& Summary Design and Develop Data Pipelines Build and optimize scalable ETL processes using PySpark or Scala or SparkSQL to handle large volumes of structured and unstructured data from diverse sources. CloudBased Data Solutions Implement data ingestion, processing, and storage solutions on the Azure cloud platform, utilizing services such as Azure Databricks, Azure Data Lake Storage, and Azure Synapse Analytics. Data Modeling and Management Develop and maintain data models, schemas, and metadata to ensure efficient data access, high query performance, and support for analytics requirements. Pipeline Monitoring and Optimization Monitor the performance of data pipelines, troubleshoot issues, and enhance workflows for scalability, reliability, and costefficiency. Security and Compliance Enforce data security protocols and compliance measures to safeguard sensitive information and meet regulatory standards.

Experience Proven track record as a Data Engineer with expertise in building and optimizing data pipelines using PySpark, SQL, and Apache Spark. Cloud Proficiency Handson experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. Programming Skills Strong proficiency in Python ,PySpark, and SQL with experience in software development practices, version control systems, and CI/CD pipelines. Data Warehousing Knowledge Familiarity with data warehousing concepts, dimensional modeling, and relational databases such as SQL Server, PostgreSQL, and MySQL. Big Data Technologies Exposure to big data frameworks and tools like Hadoop, Hive, and HBase is a plus.

Mandatory skill sets

Handson experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database. Monitor the performance of data pipelines, troubleshoot issues, and enhance workflows for scalability, reliability, and costefficiency.

Preferred skill sets

Handson experience with Azure cloud services, including Azure Databricks, Azure Data Lake Storage, Azure Synapse Analytics, and Azure SQL Database.

Years of experience required

47 years experience req.

Education qualification

B.Tech / M.Tech (Computer Science, Mathematics & Scientific Computing etc.)

Education

Degrees/Field of Study required Bachelor of Technology

Degrees/Field of Study preferred

Required Skills

Microsoft Azure Cloud Services, Microsoft Azure Databricks

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

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