IN_Manager_Data Architect_Data Analytics_Advisory_Chennai

PwC; Chennai District; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

PwC in India is seeking a Senior Data Quality Engineer to lead end-to-end quality engineering for enterprise data applications, data platforms, warehouses and lakes. You will collaborate with business stakeholders, product owners, developers and data teams to ensure data quality, build test strategies and validate data pipelines using Spark, Kafka and cloud services.

You will guide junior team members, design test data, and contribute to agile delivery cycles while ensuring release readiness and

Qualifications

• Senior Data Quality Engineer with 8-10 years of experience in data quality and testing.
• Lead end-to-end quality engineering for enterprise data applications, data platforms, data warehouses, and data lakes.
• Collaborate with business stakeholders, product owners, developers, and data engineering teams to define quality standards and acceptance criteria.

Responsibilities

• Lead testing activities across planning, test design, execution, defect tracking, release validation, and quality reporting.
• Perform manual, functional, system, integration, regression, UI, API, and end-to-end testing for data applications.
• Validate source-to-target data, transformations, business rules, completeness, accuracy, and reconciliation across data pipelines.
• Test data processing built with Apache Spark and validate input and output data from streaming or queue-based integrations such as Kafka and Kinesis.
• Create reusable test scenarios, test cases, test data, and regression suites to improve coverage and delivery efficiency.
• Use Postman for API validation and tools such as JIRA or Spira for defect lifecycle management, traceability, and reporting.
• Participate in requirement reviews and functional design discussions, perform test impact analysis, and define acceptance and quality criteria.
• Collaborate with clients, product owners, developers, and cross-functional teams to prevent defects and resolve issues within release timelines.
• Support production releases by validating functional and non-functional requirements and providing evidence for release approvals.
• Work effectively in Agile teams, contribute to ceremonies and sprint quality updates, and deliver testing within iterative release cycles.
• Guide junior team members, review testing outputs, share knowledge, and promote consistent quality engineering practices.
• Apply working knowledge of SQL and relational databases such as MySQL to perform data validation and investigation.
• Understand data lake and data warehouse concepts, including storage, security, cataloging, architecture patterns, data modelling, and star schemas.
• Have practical exposure to cloud data platforms on AWS or Azure; familiarity with services such as S3, Redshift, Glue, Athena, EMR, DMS.

Skills

SQL

Apache Spark

Postman

API testing

Kafka

Kinesis

AWS

Azure

MySQL

Tools

JIRA

Spira

S3

Redshift

Glue

Athena

EMR

DMS

Job description

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 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

Job Description & Summary: A career within.... A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations 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 :

Senior Data Quality Engineer

As a Senior Data Quality Engineer with 8-10 years of experience, you will lead end-to-end quality engineering for enterprise data applications, data platforms, data warehouses, and data lakes.

You will work closely with business stakeholders, product owners, developers, and data engineering teams to understand requirements, define quality standards, design effective test coverage, validate data pipelines, and support reliable releases in Agile delivery environments.

• Lead testing activities across planning, test design, execution, defect tracking, release validation, and quality reporting.
• Perform manual, functional, system, integration, regression, UI, API, and end-to-end testing for enterprise and data applications.
• Validate source-to-target data, transformations, business rules, completeness, accuracy, and reconciliation across data pipelines.
• Test data processing built with Apache Spark and validate input and output data from streaming or queue-based integrations such as Kafka and Kinesis.
• Create reusable test scenarios, test cases, test data, and regression suites to improve coverage and delivery efficiency.
• Use Postman for API validation and tools such as JIRA or Spira for defect lifecycle management, traceability, and reporting.
• Participate in requirement reviews and functional design discussions, perform test impact analysis, and define acceptance and quality criteria.
• Collaborate with clients, product owners, developers, and cross-functional teams to prevent defects and resolve issues within release timelines.
• Support production releases by validating functional and non-functional requirements and providing evidence for release approvals.
• Work effectively in Agile teams, contribute to ceremonies and sprint quality updates, and deliver testing within iterative release cycles.
• Guide junior team members, review testing outputs, share knowledge, and promote consistent quality engineering practices.
• Apply working knowledge of SQL and relational databases such as MySQL to perform data validation and investigation.
• Understand data lake and data warehouse concepts, including storage, security, cataloging, architecture patterns, data modelling, and star schemas.
• Have practical exposure to cloud data platforms on AWS or Azure; familiarity with services such as S3, Redshift, Glue, Athena, EMR, DMS, A