IN Senior Associate Data & Automation QA-- Data and Analytics Advisory Gurugram

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.

Responsibilities:

About the Role: We are seeking a detail-oriented and technically proficient Data QA Engineer to join our team. The ideal candidate will have strong expertise in SQL, PySpark, and data migration validation. You will play a critical role in ensuring the accuracy, integrity, and completeness of data as it moves across systems. Key Responsibilities: · Design and execute test plans and test cases for data migration projects. · Write complex SQL queries to validate data accuracy, completeness, and consistency post-migration. · Use PySpark to process and validate large datasets in distributed environments. · Collaborate with data engineers, analysts, and business stakeholders to understand data requirements and migration goals. · Identify, document, and track data quality issues and anomalies. · Automate data validation processes where applicable. · Ensure compliance with data governance and security standards. Required Skills & Qualifications: · Strong proficiency in SQL with the ability to write complex queries for data validation and analysis.

· Hands-on experience with PySpark for large-scale data processing and validation. · Proven experience in data migration projects, including source-to-target mapping and reconciliation. · Familiarity with data warehousing concepts and ETL processes. · Strong analytical and problem-solving skills. · Excellent communication and documentation skills. Preferred Qualifications: · Experience with cloud platforms (e.g., AWS, Azure, GCP). · Familiarity with data quality tools and frameworks. · Knowledge of data governance and compliance standards.

Mandatory skill sets:

QA

Preferred skill sets:

QA

Years of experience required:

6-9 years

Education qualification:

BE/BTECH, ME/MTECH, MBA, MCA

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required: Master of Business Administration, Master of Engineering, Bachelor of Technology, Bachelor of Engineering

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Quality Assurance (QA)

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, 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 {+ 28 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