Job Description

Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Senior Associate

& 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.


& Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations 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 and implement ETL/ELT pipelines using AWS services such as Lambda, Glue, EMR, and Step Functions Develop scalable data processing workflows using Python and/or PySpark Work with AWS Data Lake and Data Warehouse (e.g., S3, Redshift, Athena, Lake Formation) to ingest, transform, and store structured and semi-structured data Optimize data pipelines for performance, reliability, and cost-efficiency Collaborate with cross-functional teams in a Scrum/Agile setup to deliver sprint goals Ensure data quality, lineage, and governance through automated validation and monitoring Maintain and enhance CI/CD pipelines for data workflows Document technical designs, data flows, and operational procedures Develops, and delivers large-scale data ingestion, data processing, and data transformation projects on the Azure cloud Mentors and shares knowledge with the team to provide design reviews, discussions and prototypes Works with customers to deploy, manage, and audit standard processes for cloud products.


Mandatory skill sets:


AWS Lambda, Glue, S3, Hands on experience with Pyspark/Python on AWS,


Preferred skill sets:


Other AWS services like Redshift, Athena, and other services strong understanding of data lake and data warehouse architectures on AWS Experience with Airflow, Terraform, or CloudFormation Certification on AWS


Years of experience required:


3 to 12 years


Education qualification:


BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)

Education

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

Degrees/Field of Study required: Bachelor of Technology, MBA (Master of Business Administration), Bachelor of Engineering
Degrees/Field of Study preferred:

Certifications

(if blank, certifications not specified)

Required Skills

Data Engineering

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, 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, Data Pipeline {+ 27 more}

Desired Languages

(If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date