Data Engineer (People Analytics)

Overview

Hands-on Data Engineer joining the Global People Analytics team in Hyderabad to implement Databricks across the People data estate and then maintain and optimise it, alongside broader People Analytics data engineering work including the Workday and PRISM HR Analytics ecosystem.

What you'll do

• Act as the permanent, long-term technical owner for the Databricks platform, ensuring knowledge is retained after contract resources exit.
• Support migration of existing data pipelines and models (e.g. Workday PRISM) into the Databricks environment.
• Maintain, monitor and optimise Databricks pipelines post-implementation, and support broader People Analytics data engineering work as it arises.
• Design, build and maintain scalable batch and streaming data pipelines to support analytics and business operations.
• Write clean, efficient, 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 the Global People Analytics team.
• Safeguard end-to-end data levels of security, encryption and access protocols.
• Monitor data pipelines and solve issues in a timely, systematic manner.
• Evaluate and prototype AI agents and GenAI tools (e.g. LLMs, code generation, automated anomaly detection) to accelerate dashboard development and reduce manual fix overhead.
• Work with data scientists to identify use cases where AI agents can solve data problems at scale (e.g. self-service data quality monitoring, automated root-cause analysis).
• Document patterns, findings and standard processes around responsible AI use in the data engineering lifecycle, ensuring security, governance and ethical standards are maintained.
• Document data sources, data models, transformations, architecture design and protocol standards.
• Advocate for strong enterprise data adoption, servicing and ethical use.
• Research new data sources, methodologies, software adoption and industry standards.

What you'll need

• Minimum 3 years' experience in data engineering, analytics engineering or software engineering with a focus on data.
• Proven background in data modelling, methodologies and security design.
• Strong SQL skills and familiarity with at least one programming language.
• Hands-on and recent experience of Big Data, data warehousing, and ETL/ELT routines and concepts.
• Solid attention to detail with a drive for service excellence.
• Oral and written communication skills, with the ability to translate technical concepts for non-technical audiences and vice versa.
• Excellent problem-solving and critical thinking skills, with the ability to solve complex data pipeline activity and performance optimisation.
• Familiarity with GenAI tools and LLMs (e.g. Claude, Copilot) and curiosity about how they can enhance data workflows.
• Interest in exploring agent-based analytics and automation to solve recurring data problems.

Nice to have

• Hands-on experience with Databricks (Lakehouse architecture, Delta Lake, notebooks, workflows).
• Prior integration experience with HCM systems.
• Previous hands-on experience of Workday PRISM.
• Experience with HR systems (Workday preferred) and understanding of HR data models and business processes.
• Previous experience working with cloud-based data platforms (AWS, GCP or Azure).
• Tableau, and specifically data foundation design via Server, Pulse etc.

Details

• Location: Hyderabad, India.
• Hybrid model: 2 office days per week.