AWS Architect Data Engineering (Redshift + Glue +PySpark) - Senior Associate
Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 27, 2026. PwC UK scores B on the Alion truth index.
Industry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob 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 Senior Associate you will design and build data pipelines, integration patterns, and transformation solutions using Redshift, Glue, and PySpark within our Data and Analytics Engineering practice. As a Senior Associate you will analyze complex problems, manage assigned workstreams, build meaningful client relationships, and mentor junior team members while using critical thinking to turn data into insights that support informed decisions and business growth. In this role at PwC Acceleration Center Bangalore, you will contribute to cloud-based data architecture, work through ambiguous requirements, and apply technical skills to deliver dependable solutions across client engagements.
Responsibilities
- Designing and building cloud-based data pipelines using AWS services, Redshift, Glue, and PySpark
- Transforming raw data into curated datasets that support reporting, analytics, and downstream application use
- Developing data integration and transformation workflows across source systems, storage layers, and analytics platforms
- Creating scalable data models and warehouse structures to support performance, availability, and reuse
- Tuning SQL, Spark, and ETL processes to improve processing speed and reduce data latency
- Applying data quality checks, validation logic, and reconciliation steps across engineering deliverables
- Troubleshooting pipeline failures, data inconsistencies, and platform issues across cloud environments
- Collaborating with client teams to gather technical requirements, translate business needs, and shape delivery plans
- Reviewing work products for accuracy and mentoring junior team members on engineering methods and delivery practices
What You Must Have
- At least a Bachelor's degree
- At least 5+ 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 across Redshift, Glue, and PySpark
- Utilizing data modernization skills for cloud-based analytics platforms
- Applying ETL, data modeling, and data pipeline development knowledge
- Interpreting data to inform recommendations for client engagements
- Mentoring junior team members while navigating complex project work
Travel Requirements
Not SpecifiedJob Posting End Date