AI Led Data Engineering (AWS Redshift + Kinesis+PySpark) - Senior Associate

PwC; Andhra Pradesh; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

PwC India invites an AI Led Data Engineering Senior Associate to join the Acceleration Center India, shaping client data solutions across geographies. You’ll design data infrastructure using AWS Redshift, Kinesis, and PySpark, turning raw data into insights and supporting modernization.

You’ll analyze problems, manage workstreams, mentor juniors, and collaborate with advisory teams to deliver cloud-based data processing, integration, and transformation.

Qualifications

• At least a Bachelor's degree.
• 5+ years of data engineering experience.
• Proficient in English (oral and written).

Responsibilities

• Design and build data pipelines for cloud-based processing.
• Develop and maintain AWS Redshift, Kinesis, and PySpark solutions.
• Translate business requirements into data engineering deliverables.
• Apply data modeling, integration, and validation methods.
• Optimize pipeline performance and storage patterns.
• Support data modernization by migrating legacy flows to cloud.
• Review code to ensure engineering standards and goals.
• Collaborate with client teams to adapt solutions to changing needs.
• Mentor junior team members on tasks and problem-solving.

Skills

AWS Redshift

Kinesis

PySpark

Data pipelines

Cloud data platforms

Mentoring

Data modeling

Collaboration

Education

Bachelor's degree

Tools

AWS

Job description

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 a AI Led Data Engineering Senior Associate you will focus on building data pipelines, integration, and transformation solutions that turn raw data into actionable insights for client needs. As a Senior Associate you will analyze complex problems, manage assigned workstreams, build meaningful client connections, and guide junior team members while growing your technical skills and personal brand within our Advisory practice. In this role at PwC, you will help design and develop data infrastructure and systems using AWS Redshift, Kinesis, and PySpark, while applying critical thinking, interpreting data to shape insights, and navigating ambiguity in support of data modernization efforts.

Responsibilities

• Designing and building data pipelines that support cloud-based data processing and analytics
• Developing and maintaining AWS Redshift, Kinesis, and PySpark solutions for ingestion, transformation, and delivery
• Translating business requirements into data engineering deliverables that support client analytics and reporting needs
• Applying data modeling, integration, and validation methods to improve reliability and usability of data assets
• Optimizing pipeline performance, query execution, and storage patterns across modern data platforms
• Supporting data modernization efforts by modernizing legacy data flows into scalable cloud architectures
• Reviewing code, logic, and technical output to maintain consistency with engineering standards and project goals
• Collaborating with client teams to interpret data challenges and adjust solutions as business needs change
• Mentoring junior team members on engineering tasks, technical approaches, and problem‑solving methods

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 Redshift, Kinesis, and PySpark data engineering delivery
• Developing cloud data pipelines, transformations, and warehouse modeling
• Interpreting data to guide client recommendations and project decisions
• Collaborating across teams while managing ambiguity and changing priorities
• Mentoring junior team members through complex technical tasks