Senior Data Engineer — AI-Grade Data Infrastructure

GSK; North East; Híbrido; GBP 112.000 - 142.000; Jornada completa

Descripción de la vacante

GSK’s Enterprise AI (EAI) team invites a Senior Data Engineer to lead production data systems, shaping pipelines and AI-grade infrastructure that power multiple downstream consumers. You will define how digital workers operate within the team, establish governance and quality standards, and mentor junior engineers.

You will collaborate with FDEs and ML engineers to design real‑time data flows, ensure observability, and drive improvements in data quality and lifecycle management.

Formación

• Bachelor’s degree in Computer Science, Data Engineering or a related field, or equivalent practical experience.
• 8+ years of data engineering experience, including significant time leading the design and operation of complex production data systems.
• Expertise with modern warehouses or lakehouses, orchestration and transformation frameworks, and batch and streaming architectures, such as Databricks, BigQuery, Airflow, dbt or Spark.
• Experience leading the design of AI‑grade data infrastructure for production AI systems, including evaluation datasets, retrieval architectures and real‑time data flows.
• Experience leading data lifecycle management for AI systems, including versioning, drift monitoring and governance of AI artefacts.
• A track record of defining data quality and governance standards for a team or domain that others adopted, with measurable outcomes.
• Experience leading cloud data infrastructure design with infrastructure as code.
• Experience designing and operating AI agents or substantial LLM-powered tools inside data engineering workflows, including tool design, evaluation, observability and human‑in‑the‑loop controls.

Responsabilidades

• Lead the design of production pipelines that serve multiple downstream consumers, and define the architectural standard the team and its digital workers apply.
• Define the team’s patterns for agent-generated work within EAI’s operating model: what digital workers build and remediate, checks required, and when human review is needed.
• Design how digital workers integrate into orchestration, observability and incident workflows, with tool design, guardrails and human‑in‑the‑loop controls.
• Lead the response to significant data quality incidents, from detection to permanent resolution, and drive improvements to pipeline quality.
• Set the context standards for the team’s domains: definitions, contracts, classification and lineage in the governed context layer.
• Lead the team’s contributions to the context layer and feed operational experience into evolution of the layer.

Conocimientos

Data engineering leadership

Production data systems

Agent-based data workflows

Mentoring engineers

Cloud data infrastructure

Educación

Bachelor’s degree in Computer Science or related field

Herramientas

Databricks

BigQuery

Airflow

dbt

Spark

Descripción del empleo

GSK’s Enterprise AI (EAI) team invites a Senior Data Engineer to lead production data systems, shaping pipelines and AI-grade infrastructure that power multiple downstream consumers. You will define how digital workers operate within the team, establish governance and quality standards, and mentor junior engineers.

You will collaborate with FDEs and ML engineers to design real‑time data flows, ensure observability, and drive improvements in data quality and lifecycle management.