In - senior Associate_data Engineer_emerging Businesses_advisory_gurgaon

Data Engineer

At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. In emerging technology at PwC, you will focus on exploring and implementing cutting-edge technologies to drive innovation and transformation for clients. You will work in areas such as artificial intelligence, blockchain, and the internet of things (IoT).

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 programs, 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.

We are seeking a highly skilled and motivated Data Engineer to join our growing data engineering team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and data lake solutions using Azure Data Services, Apache Spark, and Big Data technologies. This role requires strong hands-on experience in data integration, transformation, and storage using tools such as Azure Synapse, Azure Data Factory, Databricks, SQL Server, and PySpark. The successful candidate will work closely with data scientists, analysts, and business stakeholders to ensure the availability, quality, and reliability of data assets for analytics and AI workloads.

Responsibilities:

• Design, build, and maintain scalable and reliable data pipelines using Azure Data Factory, Azure Synapse, and Databricks.
• Develop and optimize large-scale data processing jobs using PySpark and Spark SQL on Azure Databricks or Synapse Spark pools.
• Manage and work with large datasets stored in data lakes (ADLS Gen2) and integrate with enterprise data warehouses (e.g., SQL Server, Synapse).
• Implement robust data transformation, cleansing, and aggregation logic to support analytics and reporting use cases.
• Collaborate with BI developers, analysts, and data scientists to provision clean, reliable, and timely datasets.
• Optimize data flows for performance and cost efficiency on Azure cloud platforms.
• Implement data governance, lineage, and security practices across the data architecture.
• Troubleshoot and resolve data pipeline failures and ensure high availability and fault-tolerant design.
• Participate in code reviews, adhere to version control practices, and maintain high coding standards.

Mandatory skill sets:

• Azure Data Factory (ADF), Azure Synapse Analytics, Azure Databricks
• Apache Spark, PySpark
• SQL Server / T-SQL / Synapse SQL
• Azure Data Lake Storage Gen2
• Big Data ecosystem knowledge (Parquet, Delta Lake, etc.)
• Git, DevOps pipelines for data engineering
• Performance tuning of Spark jobs and SQL queries

Preferred skill sets:

• Python for data engineering workflows
• Azure Monitor, Log Analytics for pipeline observability
• Power BI (data modeling, DAX)
• Delta Lake
• Experience with CI/CD for data pipelines (YAML pipelines, ADF integration)
• Knowledge of data quality tools and frameworks

Years of experience required: 4 to 8 years

Education qualification:

• B.E/B.Tech/M.Tech in Computer Science, Information Technology, or related fields
• MCA with relevant data engineering experience

Degrees/Field of Study required: MBA (Master of Business Administration)

Degrees/Field of Study preferred:

Bachelor of Engineering Degrees/Field of Study

Required Skills: Data Engineering

Optional Skills: Accepting Feedback, Active Listening, Analytical Thinking, Artificial Intelligence, Business Planning and Simulation (BW-BPS), Communication, Creativity, Digital Transformation, Embracing Change, Emotional Regulation, Empathy, Implementing Technology, Inclusion, Innovation Processes, Intellectual Curiosity, Internet of Things (IoT), Learning Agility, Optimism, Product Development, Product Testing, Prototyping, Quality Assurance Process Management

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