
Advisory
Not Applicable
Data, Analytics & AI
Senior Associate
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 decision-making 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
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.
We are seeking an experienced Senior Data Engineer / ETL QA Engineer with strong hands-on expertise in Snowflake, SQL, AWS/GCP, ETL testing, data warehousing, data analysis, Python, Microsoft Fabric, and Azure Data Factory. The role requires the ability to design, develop, validate, optimize, and support scalable data pipelines and backend data solutions while ensuring high-quality, reliable, and secure data delivery for the US Healthcare domain.
Data Engineering & Integration: Design, develop, and optimize scalable backend data solutions and ETL/ELT pipelines using Snowflake, SQL, AWS/GCP, Python, Microsoft Fabric, and Azure Data Factory.
ETL Testing & Data Validation: Perform end-to-end ETL testing, data analysis, validation, reconciliation, and defect analysis across data warehouse environments using complex SQL queries.
Snowflake & Cloud Development: Build and support Snowflake-based solutions, including performance tuning, workload optimization, and integration with AWS services such as CloudWatch, Lambda, Glue, and EMR clusters.
ETL Process Ownership: Demonstrate end-to-end understanding of ETL processes, complex job flows, data flows, day-to-day loads, and operational dependencies across the project.
Issue Analysis & Production Support: Analyze daily load issues, job failures, defects, and escalations; take corrective actions and document complex issues for resolution and future reference.
Testing Methodology & Defect Management: Apply strong testing methodology, use defect tracking tools effectively, and ensure data quality, accuracy, completeness, and reliability across the data lifecycle.
Agile Collaboration: Work in an agile delivery model with data engineers, QA teams, business analysts, and stakeholders; demonstrate strong strategic thinking, problem-solving, communication, and analytical skills.
Healthcare Domain Alignment: Apply working knowledge of US Healthcare data, workflows, and reporting needs to support testing, analysis, and data platform modernization initiatives.
5 to 8 years
Why Join Us?
BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Technology, Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Amazon Web Services (AWS), Data Engineering
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 Development, 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}
Desired Languages (If blank, desired languages not specified)
Available for Work Visa Sponsorship?
Government Clearance Required?
August 24, 2026

At PwC, we help clients drive their companies to the leading edge. We’re a tech-forward, people-empowered network with more than 370,000 people in 149 countries. Across audit and assurance, tax and legal, deals and consulting we help build, accelerate and sustain momentum. Find out more at www.pwc.com.
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