Data Engineer
Summary
Build and optimize cloud-based data pipelines and ETL/ELT workflows using Python, PySpark, and Azure/AWS services to deliver clean, reliable data for analytics and AI solutions.
IN-Senior Associate_Data Engineer_D&A_ Advisory_ Bangalore
Location: Bengaluru Millenia
Time Type: Full time
Job Description
Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob Description & Summary
At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.
*Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.
At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "
Responsibilities
Data Pipeline & Architecture Development
Pipeline Engineering: Develop robust systems to ingest, cleanse, and normalize diverse datasets. Build highly efficient ETL/ELT pipelines to structure previously unstructured data from various internal and external sources.
Architecture Best Practices: Define and implement data architecture standards ensuring the scalability, high availability, and security of enterprise data lakes, data warehouses, and related cloud components.
Performance Tuning: Identify bottlenecks in data pipelines, ETL processes, and complex queries. Propose and implement optimization strategies to maximize system performance and facilitate timely data ingestion.
Data Integrity: Conduct rigorous data profiling, validation, and quality checks to ensure absolute data consistency and accuracy across all platforms.
Documentation & Governance: Develop and maintain comprehensive documentation covering data flows, data dictionaries, data lineage, and integration processes.
Mandatory skill sets:
Programming & Big Data: Python, PySpark, Apache Spark, Spark Streaming
Cloud Platforms: Microsoft Azure (Preferred), AWS
Distributed Computing: Databricks, Azure HDInsight, AWS EMR, AWS Glue
Databases (Relational & NoSQL): Azure SQL Server, Cosmos DB, MongoDB
Data Ingestion & Storage: Azure Data Lake Storage (ADLS), Azure Event Hubs, Azure Search, Streaming Technologies
DevOps: CI/CD pipelines, Source Code Control systems (e.g., Git)
Core Data Engineering: ETL/ELT optimization, Data Modeling, Data Profiling, Data Governance
Preferred skill sets:
Programming & Big Data: Python, PySpark, Apache Spark, Spark Streaming
Cloud Platforms: Microsoft Azure (Preferred), AWS
Distributed Computing: Databricks, Azure HDInsight, AWS EMR, AWS Glue
Databases (Relational & NoSQL): Azure SQL Server, Cosmos DB, MongoDB
Data Ingestion & Storage: Azure Data Lake Storage (ADLS), Azure Event Hubs, Azure Search, Streaming Technologies
DevOps: CI/CD pipelines, Source Code Control systems (e.g., Git)
Core Data Engineering: ETL/ELT optimization, Data Modeling, Data Profiling, Data Governance
Years of experience required: 5+ years of overall professional work experience in a technical data role.
3+ years of active, hands-on development experience as a data developer building robust pipelines using the technologies listed above.
Education qualification: Bachelor’s degree in Computer Science, Information Science, Mathematics, Statistics, or a related quantitative discipline.
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Business AdministrationDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Data EngineeringOptional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytical Thinking, Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Creativity, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline {+ 38 more}Desired Languages (If blank, desired languages not specified)
Travel Requirements
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date
July 16, 2026