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. "

Role:

Data Engineer with 4-8 years of hands-on experience in designing, building and optimizing data pipelines on Cloud.

Responsibilities:

• Design, develop, and maintain high performance ETL/ELT pipelines using Pyspark, Python, SQL • Build & optimize distributed data processing workflows on cloud platforms (GCP or Azure) • Develop and maintain batch and real-time ingestion including integration with Kafka • Ensure Data Quality and metadata management across data pipelines • Monitor and tune data systems and queries for optimal performance, cost efficiency, and reliability. • Automate data workflows and processes using tools like Cloud Composer (Apache Airflow) and leverage Cloud Monitoring/Logging for troubleshooting and operational efficiency.

Mandatory skill sets:

• Data engineering with 4-8 years of experience with strong proficiency in PySpark, Python, SQL. • Hands-on experience with GCP especially on the services like BigQuery, DataProc, Cloud Storage, Composer, Dataflow • Strong understanding of data warehousing concepts, data modelling & ETL/ELT processes and expertise in Datawarehouse / Datalake / lakehouse architecture • Familiarity with big data processing frameworks like Apache Spark and should have experience in Apache Kafka • Experience with version control tools like Git and CI/CD pipelines.

Preferred skill sets:

• Experiences with DBT – in building models, testing & deployments • Should have knowledge on Data modelling • Good to have exposure on Docker and deployments on GCP • Good to have hands-on with Pub/sub, Cloud run • Exposure to streaming workloads • Good to have hands-on exposure Java – core Other Expectations: • Analytical and problem-solving skills • Ability to work in agile • Communication and stakeholder management skills • Accountability & ownership

Years of experience required:

4 to 8

Education qualification:

BE , B.Tech

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

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

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

PySpark

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 {+ 27 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