Line of Service
Advisory

Industry/Sector
Not Applicable

Specialism
Data, Analytics & AI

Management Level
Manager

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 PWCAt 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: A career within…. A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. 

Responsibilities:

Define and lead test strategies for data-intensive systems, ensuring alignment with quality and compliance goals.

Design and implement scalable automation frameworks for ETL/ELT pipelines and cloud-based data platforms.

Guide a team of QA engineers, driving best practices in test automation, data validation, and performance testing.

Integrate automated tests into CI/CD workflows using tools like Jenkins, GitHub Actions, or Azure DevOps.

Collaborate with engineering, data, and business teams in Agile environments to ensure quality across the development lifecycle.

Report key QA metrics and provide risk-based recommendations for release readiness.

Stay current with testing trends, including AI-powered automation tools.

Mandatory skill sets:

Strong background in ETL testing, data quality, and SQL.

Experience with ETL tools

Proficiency in test automation (Python, Java, PyTest, Selenium).

Solid understanding of cloud platforms (AWS, Azure) and CI/CD.

Familiar with Agile/Scrum practices and stakeholder collaboration.

Preferred skill sets:

Working knowledge of AWS.

Understanding of DevOps practices

Team Handling

Client Facing

Years of experience required:

8-12

Education qualification:

B.Tech / M.Tech / MBA / MCA

Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Engineering, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills
QA Automation

Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Coaching and Feedback, 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 + 32 more

Desired Languages (If blank, desired languages not specified)

Travel Requirements
Not Specified

Available for Work Visa Sponsorship
No

Government Clearance Required
No

Job Posting End Date
April 2, 2026

IN_Manager_QA Automation_Data Analytics_Advisory_Bangalore