Manager - AWS Data Engineer

IN- Manager_AWS Data Engineer _Data Analytics_ Advisory_ Bangalore

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & 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 PWC

At 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 us.

At 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. "

Job Description & Summary: A career within…. A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations 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, develop, and maintain ETL/ELT pipelines using AWS services (Glue, Lambda, Step Functions, Data Pipeline, EMR). 

• Build and optimize data lakes and data warehouses using Amazon S3, Redshift, Athena, and Snowflake (if applicable). 

• Implement and manage data ingestion frameworks from structured and unstructured data sources (APIs, RDBMS, streaming, etc.). 

• Ensure data quality, integrity, and security using tools like AWS Lake Formation, IAM, and KMS. 

• Strong proficiency in SQL, Python, and PySpark. 

• Expertise in AWS data ecosystem – including Glue, Redshift, S3, Lambda, EMR, and Athena. 

Mandatory skill sets: 

 

• Strong proficiency in SQL, Python, and PySpark. 

• Expertise in AWS data ecosystem – including Glue, Redshift, S3, Lambda, EMR, and Athena. 

 

 

Preferred skill sets: 

 

• AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect. 

 

Years of experience required: 

 

7-11 

Education qualification: 

 

B.Tech / M.Tech / MBA / MCA 

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

Degrees/Field of Study required: Bachelor of Engineering, Master of Business AdministrationDegrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

AWS Devops

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

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

April 14, 2026

Experience Level

Mid Level