Senior Data Engineer — AI-Grade Data Infrastructure Lead

GlaxoSmithKline; United States; Hybrid; USD 140,000 - 210,000; Full time

Job summary

GlaxoSmithKline seeks a Senior Data Engineer to design production data systems for AI-driven teams. You will define architectural standards, govern data quality, and lead AI-grade data infrastructure including real-time data flows and evaluation datasets.

You will mentor junior engineers, collaborate with ML and AI product teams, and drive cloud-based, Infrastructure as Code strategies to improve deployment reliability.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering or a related field, or equivalent practical experience
• 8+ years of data engineering experience leading 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 and real-time data flows
• Experience leading data lifecycle management for AI systems, including versioning, drift monitoring and governance of AI artefacts
• Track record of defining data quality and governance standards for a team or domain with measurable outcomes
• Experience leading cloud data infrastructure design with infrastructure as code
• Experience designing and operating AI agents or LLM-powered tools inside data engineering workflows
• Experience mentoring junior and mid-level engineers

Responsibilities

• Lead the design of production pipelines serving multiple downstream consumers and define architectural standards
• Define patterns for agent-generated work within the operating model
• Design how digital workers integrate into orchestration, observability, and incident workflows
• Lead response to significant data quality incidents and drive improvements in pipeline quality
• Set context standards for definitions, contracts, and lineage in the governed context layer
• Lead contributions to the context layer and its evolution across EAI
• Define data quality and governance standards and drive adoption
• Lead AI-grade data infrastructure design including evaluation datasets and retrieval architectures
• Oversee data lifecycle management for AI systems including versioning and governance
• Lead cloud data infrastructure design and promote infrastructure as code adoption
• Build platform components for multiple engineers and digital workers
• Raise the operational bar across testing, CI/CD, observability, and on-call practices
• Set documentation and code quality standards and mentor engineers
• Partner with FDEs, ML engineers and AI product teams on data requirements

Skills

Data Analysis

Data Modeling

SQL

ETL Development

Data Governance

Data Ingestion

Data Integration

Data Architecture

Python

Databricks

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

BigQuery

Airflow

dbt

Spark

Job description

GlaxoSmithKline seeks a Senior Data Engineer to design production data systems for AI-driven teams. You will define architectural standards, govern data quality, and lead AI-grade data infrastructure including real-time data flows and evaluation datasets.

You will mentor junior engineers, collaborate with ML and AI product teams, and drive cloud-based, Infrastructure as Code strategies to improve deployment reliability.