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. "

 

Job Description & Summary: A career within PWC

Responsibilities:

Experience:3-8 years in Data Engineering Job Summary We are looking for a skilled and motivated Data Engineer with strong hands-on experience in Databricks, PySpark, and cloud-based data platforms. The ideal candidate will be responsible for designing and developing scalable data pipelines and solutions that support advanced analytics and business intelligence initiatives. This role requires a deep understanding of cloud data lakes, data warehousing, and modern data engineering practices. --- Key Responsibilities · Design and develop data pipelines using Databricks and PySpark to ingest, process, and transform large volumes of data. · Implement ETL/ELT workflows to move data from source systems to Data Warehouses, Data Lakes, and Lake Houses using cloud-native tools. · Work with structured and unstructured data stored in AWS or Azure Data Lakes. · Apply strong SQL and Python skills to manipulate and analyze data efficiently. · Collaborate with cross-functional teams to deliver cloud-based serverless data solutions. · Design innovative data solutions that address complex business requirements and support data-driven decision-making. · Maintain documentation and enforce best practices for data architecture, governance, and performance optimization.

Preferred Qualifications: · Bachelor’s degree in Computer Science, Information Technology, or related field. · 4+ years of hands-on project experience in Databricks, PySpark, and SQL on any cloud platform (AWS or Azure). · Strong programming skills in Python. · In-depth knowledge of Data Warehousing, Database technologies, and Big Data ecosystem. · Proven experience working with cloud-based data lakes (Azure Data Lake Storage Gen2 or AWS S3). · Familiarity with DevOps practices including CI/CD, Infrastructure as Code (IaC), and automation is a plus. Development experience Design and Develop Data Pipelines: Create pipelines to ingest, process, and transform data, deliver Cloud-based Serverless solutions to the customers. Design Data Solutions: Leverage your analytical skills to design innovative data solutions that address complex business requirements and drive decision-making.

Mandatory

skill sets:

PySpark, Databricks

Preferred

skill sets:

PySpark, Databricks

Years of

experience

required:

3-8 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: Bachelor of Engineering, Bachelor of Technology, Master of Business Administration

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 {+ 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