Senior Data Engineer

GSK's Data & Analytics team is seeking a Senior Data Engineer to lead key activities in building and maintaining a scalable data foundation, creating data products for analytics and AI, ensuring data accuracy and trustworthiness, and turning business questions into data solutions.

Responsibilities:

• Design, build, and run scalable data pipelines that collect, clean, transform, and deliver data
• Build reusable datasets, feature tables, and retrieval infrastructure to support dashboards, models, and AI applications
• Implement data quality checks, validation rules, monitoring, and alerting to ensure data accuracy and trustworthiness
• Work with business partners, data scientists, and analysts to gather requirements and deliver self-service data
• Prepare data for modeling and create, version, and maintain training and evaluation datasets
• Automate data checks, monitoring, and reporting using AI tools and agents
• Investigate pipeline and data incidents, find root causes, and implement lasting fixes
• Set standards for code, documentation, and governance, and conduct code reviews and mentorship
• Refine frameworks, tools, and automation to reduce manual effort and stay current with emerging data and AI engineering practices

Requirements:

• Experience designing ETL/ELT pipelines and orchestrating them with Azure Data Factory, Databricks Workflows
• Experience with Git, Azure DevOps, CI/CD pipelines, and automated testing for data code
• Experience implementing data quality checks, monitoring, and data cataloging or governance
• Solid understanding of data modeling, dimensional models, data warehouses, lakehouse architecture
• Working knowledge of Power BI or similar tools for serving data to business users

Preferred Skills:

• 5+ years of experience as a data engineer, including building and operating production data pipelines
• Experience supporting data scientists or analysts and translating their needs into reliable datasets
• Strong SQL and Python, including PySpark for large-scale data processing
• Hands-on experience with Azure Databricks, Delta tables, Unity Catalog, Databricks Workflows, and SQL Warehouses
• Experience supporting ML projects using Azure ML, MLflow, or Databricks