16 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Develop data pipelines and transformation logic using AWS Redshift, AWS Glue, and PySpark.
- Design and maintain data integration workflows that move source-system information into analytics-ready environments.
- Build reusable ETL components for cloud-based data modernization initiatives.
- Write and tune SQL and PySpark code to improve query performance and processing speed.
- Validate data quality through checks and reconciliation while troubleshooting pipeline issues.
- Support data modeling for warehouse and lakehouse structures.
- Translate business needs into data engineering tasks with technical and client teams.
- Apply AWS services and data tooling to implement scalable data infrastructure.
- Document pipeline logic, technical dependencies, and deployment steps.
- Learn new methods and tools to support delivery across data engineering engagements.
Requirements
- Bachelor's degree required.
- At least 3+ years of experience required.
- Oral and written proficiency in English required.
- Preference for study in fields including management information systems, computer and information science, systems engineering, engineering, mathematics, or statistics.
- Coursework or internship exposure in data engineering is preferred.
- Experience using AWS, Redshift, Glue, or PySpark in academic projects is preferred.
- Understanding of data pipelines, transformations, and data warehouse concepts is preferred.
- Problem-solving, critical thinking, collaboration, and ability to learn quickly are preferred.
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.