AWS Architect Data Engineering (Kinesis+ Redshift + Glue +PySpark) - Senior Manager

Industry/Sector

Not Applicable

Specialism

Analytics

Management Level

Senior 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 AWS Architect Data Engineering you will lead the design and delivery of data engineering solutions using Kinesis, Redshift, Glue, and PySpark, translating business needs into cloud-based data pipelines and analytics-ready platforms within our Advisory practice. As a Senior Manager you will lead large projects, guide teams through complex technical work, and use sound judgment, clear communication, and coaching to drive results across stakeholders and delivery teams. In this role at PwC, you will help shape scalable data infrastructure, support client needs, and bring structure to data integration and transformation efforts that turn raw data into actionable insights.



Responsibilities

- Leading AWS-based data engineering workstreams across client engagements and translating data modernization goals into actionable solution designs
- Architecting data pipelines and data integration patterns using Kinesis, Redshift, Glue, and PySpark for batch and streaming use cases
- Designing cloud data platforms that support ingestion, transformation, storage, and downstream analytics across enterprise environments
- Guiding technical teams through complex migration and modernization efforts, balancing delivery needs, risks, and dependencies
- Reviewing data architecture choices, performance tuning approaches, and data quality controls to improve reliability and processing efficiency
- Advising clients on scalable lake, warehouse, and transformation solutions that support reporting, analytics, and business insight
- Applying hands-on knowledge of AWS services and data engineering platforms to shape implementation plans and resolve architecture issues
- Coaching team members on delivery methods, technical tradeoffs, and documentation standards across multiple workstreams
- Collaborating with stakeholders to validate solution direction, clarify requirements, and align technical outcomes with business priorities
- Driving continuous improvement in data engineering processes, reusable components, and deployment practices

What You Must Have

- At least a Bachelor's degree
- At least 13+ 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
- Demonstrating AWS data engineering experience using Kinesis, Redshift, and Glue
- Applying PySpark for scalable data transformation and analytics pipelines
- Leading client-facing modernization efforts across cloud data platforms
- Translating complex architecture choices into clear stakeholder messaging
- Coaching teams through ambiguity, prioritizing decisions, and resolving blockers

Travel Requirements

Not Specified

Job Posting End Date