Engineer II, Data Engineer

About the role

Enterprise AI (EAI) builds the data foundations that GSK's AI systems depend on. In our operating model, digital workers do the hands-on data engineering. They generate pipelines, test and deploy them, monitor them in production and remediate failures. Humans and digital workers both rely on a governed context layer.

What you'll do

• Design pipelines for complex use cases and direct digital workers to build and operate them, with clear, defensible architectural trade-offs
• Own the quality of agent-generated work in your domain: review, test and approve it within the remit EAI's operating model sets, and escalate what falls outside it
• Improve how digital workers operate in your domain by refining the frameworks, tools and evaluations they use
• Own the context for your domain in the governed context layer: definitions, contracts, lineage and governance documentation that humans and digital workers rely on
• Contribute reusable components to the context layer, such as metadata enrichment, classification or lineage capture, that other domains can adopt

What you need

• 10–18 yrs of experience
• SQL
• Python
• ETL
• Databricks
• LLMs
• BigQuery
• B.Sc or B.Tech or B.E. or BCA

Good to have

• Airflow
• dbt
• Spark
• Terraform
• Incident response