Principal Data Engineer

Overview

Principal Data Engineer role within GSK's Data & Analytics team, responsible for building and running production-grade data pipelines and data products for analytics and AI.

What you'll do

• Design, build, and run scalable, production-grade data pipelines that collect, clean, transform, and deliver data, and make sound architectural choices.
• Build reusable datasets, feature tables, and where needed retrieval infrastructure (such as vector databases) supporting dashboards, models, and AI applications, and define clear data contracts.
• Implement data quality checks, validation rules, monitoring, and alerting, and track data lineage.
• Work with business partners, data scientists, and analysts to gather requirements, agree delivery timelines and service levels, and deliver self-service data.
• Create, version, and maintain training and evaluation datasets used by data scientists, ensuring reproducible results.
• Build or use LLM-powered tools and agents to automate data checks, monitoring, and reporting, and set guardrails.
• Investigate pipeline and data incidents, find root causes, and implement lasting fixes.
• Set standards for code, documentation, and governance, conduct code reviews, and mentor junior and mid-level engineers.
• Refine frameworks, tools, and automation to reduce manual effort.

What you'll need

• 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 (complex queries, performance tuning) 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 designing ETL/ELT pipelines and orchestrating them with Azure Data Factory and Databricks Workflows.
• Experience with Git, Azure DevOps (or GitHub) CI/CD pipelines, and automated testing for data code.
• Experience implementing data quality checks, monitoring, and data cataloging or governance (for example Collibra or Unity Catalog).
• Solid understanding of data modeling (dimensional models, data warehouses, lakehouse architecture).

Nice to have

• Experience supporting ML projects using Azure ML, MLflow, or Databricks (feature tables, MLOps, dataset versioning, vector search, RAG pipelines).
• Experience building LLM-based automation or AI agents, or using Databricks Genie for self-service analytics.
• Working knowledge of Power BI or similar tools for serving data to business users.

Details

• Location: Bengaluru Luxor North Tower.