Job Description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

& 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 PWCAt 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 usAt 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. "

& Summary:

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:

• Design, build, and maintain scalable data pipelines and ETL processes in AWS cloud environments.

• Develop and manage file movement, data ingestion, and streaming solutions using AWS services such as Glue, Kinesis, Lambda, and Athena.

• Implement and maintain data storage and processing solutions using AWS data services including Redshift, Aurora, RDS, S3, and related services.

• Develop serverless and distributed data processing solutions using Python, Spark, and AWS Lambda.

• Orchestrate workflows and pipelines using Apache Airflow and automation tools.

• Implement CI/CD pipelines, version control, and automation using Jenkins, GitHub, and other DevOps platforms.

• Ensure data security, access control, governance, and compliance by managing AWS security policies and access management.

• Collaborate with cross-functional teams in an Agile environment to deliver reliable, high-quality data solutions.

• Troubleshoot complex data issues and optimize performance of data workflows and systems.

Mandatory skill sets:

 Experience

• 6+ years of proven experience as a Data Engineer, preferably in cloud-based environments

 AWS & Cloud Technologies

• AWS Glue, Athena, Lambda, Kinesis

• AWS integration and ETL stack

• AWS data services: Redshift, Aurora, RDS, S3

• Security, IAM, policies, and access management in AWS

 Programming & Data Processing

• Python

• Apache Spark

• AWS Lambda development

 DevOps & Automation

• CI/CD pipelines

• Jenkins

• GitHub

• Automation platforms

 Workflow & Infrastructure Tools

• Apache Airflow

• Ansible

 Data Engineering Fundamentals

• Data modeling

• Data warehousing concepts

• Data architecture best practices

 Methodologies

• Agile Development

Preferred skill sets:

• Experience with real-time data streaming architectures

• Exposure to advanced AWS analytics services and performance optimization

• Strong problem-solving and analytical abilities

• Excellent communication and collaboration skills

• Ability to work effectively in fast-paced, dynamic environments

Years of experience required:

6+ years of Data Engineering experience (Cloud/AWS preferred)

Education qualification:

BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)

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

Degrees/Field of Study required: Bachelor of Engineering, Master of Engineering, MBA (Master of Business Administration)Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Big 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, 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

May 21, 2026