AI Led Data Engineering Manager - Multiple Teams

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

The Opportunity

Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.

As an AI Led Data Engineering Manager you will design and build data infrastructure, pipelines, integration layers, and transformation solutions that help clients turn raw data into usable insights within our Advisory practice. As a Manager you will lead teams, coach junior professionals, manage engagement workstreams, and apply judgment to complex problems while balancing timelines, quality, and client expectations. In this role at PwC, you will work across AWS data tools such as Kinesis, Redshift, Glue, and PySpark to deliver data engineering solutions that support analytics and business decision-making, while also identifying opportunities to improve delivery methods and apply technology in practical ways.



Responsibilities

- Leading data engineering workstreams across cloud-based platforms and advanced analytics solutions
- Managing client deliverables, timelines, and budgets for data pipeline and data integration projects
- Designing and building scalable data infrastructure using AWS, Kinesis, Redshift, Glue, and PySpark
- Developing batch and streaming pipelines that support data transformation, validation, and loading
- Overseeing data architecture, modeling, and warehouse design for modernized data environments
- Reviewing technical deliverables to validate data quality, performance tuning, and secure handling of data
- Coaching team members on engineering methods, delivery planning, and use of automation tools
- Identifying opportunities to improve data modernization strategies through cloud migration and platform optimization

What You Must Have

- At least a Bachelor's degree
- At least 9+ years of experience
- Oral and written proficiency in English required

What Sets You Apart

- Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
- Leading AI-driven data engineering initiatives across Kinesis, Redshift, Glue, and PySpark
- Managing client-facing data modernization workstreams with cloud-native platforms
- Translating system dependencies into scalable data architecture decisions
- Mentoring teams in data pipeline design, testing, and performance tuning
- Coordinating Agile delivery across multiple stakeholders and timelines

Travel Requirements

Not Specified

Job Posting End Date