Industry/Sector
Not Applicable
Specialism
Product Innovation
Management Level
Senior Associate
Job Description & Summary
The Prospect

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 a GCP Data Engineer - Senior Associate you will design and support data pipelines, cloud data platforms, and ETL solutions within our Advisory practice. As a Senior Associate you will analyze complex data problems, manage assigned workstreams, and contribute to client-facing delivery while building meaningful client relationships and mentoring junior team members. In this role at PwC,



you will help modernize data environments using Google Cloud Platform, Databricks, Snowflake, and hybrid cloud tools, while developing your technical skills and broader business understanding across cloud engineering and data modernization.

Responsibilities
- Building GCP data pipelines and cloud-native data solutions to support modernization initiatives
- Designing and implementing data integration, transformation, and validation workflows across source systems
- Developing scalable data lake and data warehouse structures for analytics and reporting use cases
- Optimizing pipeline performance, query execution, and storage design in cloud environments
- Applying Apache Airflow, Databricks, and Snowflake to automate orchestration and data delivery
- Collaborating with client stakeholders to translate business needs into technical data engineering deliverables
- Reviewing code, data models, and deployment outputs to maintain technical consistency ac

📌 GCP Data Engineer (Hyderabad)
🏢 PwC
📍 Hyderabad