PwC—IN-Manager · Senior Data Technical Lead · D&A · Advisory · Hyderabad

Job description

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: 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, Airflow, or equivalent services is advantageous.  Demonstrate basic programming knowledge in Python or PySpark and collaborate effectively with data engineering teams on technical troubleshooting.  Communicate clearly with technical and business stakeholders, manage multiple work tracks, and demonstrate strong ownership, interpersonal skills, and continuous learning.  Exposure to test automation, reporting tools such as Power BI or QuickSight, emerging technologies, Generative AI, or relevant data and quality certifications is an added advantage.  Mandatory skill sets: Testing, Test Design, Defect Tracking, Preferred skill sets: Python, Pyspark Years of experience required: 8-10yrs Education qualification: B.Tech / M.Tech / M.E / MCA/B.E Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Technology, Bachelor of Engineering Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Azure Service Fabric, 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, 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 Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date August 26, 2026