PwC

IN_Sr Associate – Senior Data Engineer / ETL QA Engineer – D&A– Advisory – Gurgaon

PwC Gurugram, Haryana, India

Professional Services · 10,001+ employees

14 h ago
qa Senior (5-10 yrs) Full-time India
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About the role

Design, develop, and optimize scalable backend data solutions and ETL/ELT pipelines using cloud technologies. Perform end-to-end ETL testing, data validation, and production support to ensure high-quality data delivery for the US Healthcare domain.

What they look for

Snowflake SQL AWS GCP ETL Testing Data Warehousing Data Analysis Python Microsoft Fabric Azure Data Factory Data Engineering Performance Tuning Agile Methodology Data Pipelines US Healthcare Domain Defect Tracking

Requirements

Requires 5 to 8 years of hands-on experience in ETL testing, data warehousing, and SQL-based validation. Candidates must possess strong expertise in Snowflake, cloud platforms like AWS/GCP, and modern data integration frameworks.

Benefits

Inclusive benefits Flexibility programmes Mentorship Wellbeing support

Full description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

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.

Job Description & Summary:  

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. 

Responsibilities: 

 

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. 

 

Mandatory skill sets: 

 

  • 5+ years of hands-on experience in ETL testing, data warehousing, data analysis, and SQL-based validation 
  • Strong expertise in Snowflake, SQL, Unix, complex query writing, and Snowflake performance tuning 
  • Hands-on cloud experience with AWS/GCP, including AWS services such as CloudWatch, Lambda, Glue, and EMR clusters 
  • Working knowledge of Python, Microsoft Fabric, Azure Data Factory, and modern ETL/ELT frameworks 

 

Preferred skill sets: 

 

  • Strong understanding of US Healthcare data, defect tracking tools, agile methodology, AEDL dashboard setup exposure, and production support processes 

 

Years of experience required: 

 

5 to 8 years 

 

Why Join Us? 

  • Work on a high-impact data transformation and AI readiness program 
  • Exposure to modern data stack (Snowflake + Salesforce ecosystem) 
  • Opportunity to shape enterprise-wide data integration architecture 

 

Education qualification: 

 

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)

Required Skills

Amazon Web Services (AWS), Data Engineering

Optional Skills

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)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

August 24, 2026

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