The Opportunity
Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.
As an AI Led Data Engineer, you will design and build data pipelines, data integration, and data transformation solutions using AWS Redshift, Glue, and PySpark within our Data and Analytics Engineering practice. As an Associate, you will focus on learning, contributing to client support work, and building your skills while navigating complex data challenges, using critical thinking, adaptability, and curiosity to support project delivery and develop your technical acumen. In this role at PwC, you will help transform raw data into actionable insights, support the development of data infrastructure and systems, interpret data to inform recommendations, and contribute to work that supports informed decision-making and business growth.
Responsibilities
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Developing data pipelines and transformation logic using AWS Redshift, Glue, and PySpark
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Designing and maintaining data integration workflows that move information from source systems into analytics-ready environments
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Building reusable ETL components to support cloud-based data modernization initiatives
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Writing and tuning SQL and PySpark code to improve query performance and processing speed
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Validating data quality through checks, reconciliation steps, and troubleshooting of pipeline issues
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Supporting data modeling activities for warehouse and lakehouse structures
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Collaborating with technical and client teams to translate business needs into data engineering tasks
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Applying AWS services and data tooling to help implement scalable data infrastructure
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Documenting pipeline logic, technical dependencies, and deployment steps for ongoing support
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Learning new methods and tools to contribute to delivery across data engineering engagements
What You Must Have
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At least a Bachelor's degree
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At least 3+ years of experience
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Oral and written proficiency in English required
What Sets You Apart
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Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
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Demonstrating coursework or internship exposure in data engineering
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Utilizing AWS, Redshift, Glue, or PySpark in academic projects
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Interpreting data pipelines, transformations, and data warehouse concepts
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Applying problem-solving and critical thinking to technical tasks
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Collaborating in fast-paced project settings and learning quickly
