Data Engineer (People Analytics)

OVERVIEW OF THE ROLE

We are looking for an experienced?hands-on Data Engineer?to join our Global People Analytics team in Hyderabad. In this role, youll be instrumental in designing, building, and maintaining scalable data pipelines, data modelling and will be a key technical contributor on all aspects of the end-to-end data management lifecycle. The successful candidate will architect robust data solutions and models that support our Workday and PRISM HR Analytics ecosystem. As the Analytics function evolves, you will help shape our roadmap through data lead strategies and technology adoption such as GenAI, Tableau, AWS Data Bricks with the People Analytics data foundation being a key enabler.

In addition, we are looking for someone who will find the right balance between maximising security without hindering productivity. With a pragmatic approach to problem solving and what makes sense to the business and holistic interoperability.

If youre excited by a challenge, a critical thinker with a strong passion for data driven decision making, then wed love to hear from you.

KEY RESPONSIBILITIES

• Design, build, and maintain scalable batch and streaming data pipelines to support analytics and business operations.
• Write clean, efficient, and well-documented code and ETL/ELT processes.
• Ensure data is dependable, accurate, and delivered in a timely manner.
• Work with information technicians, data scientists, and product managers to understand requirements and deliver actionable data solutions.
• Translate business needs into tangible engineering outcomes.
• Participate in code reviews, sprint planning, Project lifecycles, and retrospectives as part of a Global People Analytics Team
• Safeguard end-to-end Rested and Transit data levels of security, encryption, and access protocols.
• Monitor data pipelines and troubleshoot issues in a timely, systematic manner.
• Document data sources, data models, transformations, architecture design, and best practice standards.
• Advocate and ambassador for strong enterprise data adoption, servicing, and ethical use.
• Research new data sources, methodologies, software adoption, and industry standards.