Principal Data Engineer

Overview

Principal Data Engineer for Global Drug Safety within GSK R&D Tech, leading design, development and delivery of Drug Safety data products and shaping GSK's future Drug Safety and data platforms.

What you'll do

• Design and implement end-to-end, AI-driven data pipelines that ingest, transform, and analyze safety data from multiple sources.
• Lead building enterprise data platforms with modern AI-Native solutions using technologies such as RAG, Vector Databases, Agentic AI, LLMOps, LangChain, LangGraph, Semantic Search, AI Agents, and Azure OpenAI.
• Build scalable solutions that replace labor-intensive tasks with automated workflows, reducing processing time and errors.
• Collaborate with the Product Owner and cross-functional teams to align technical solutions with the strategic product roadmap.
• Deliver the optimal set of products and services that meet business strategy and requirements, and execute the product roadmap.
• Develop novel approaches to extract actionable insights from complex data sets, optimize data quality, drive signal detection, and support regulatory reporting.
• Ensure solutions adhere to best practices in software development, including robust testing, code documentation, and DevOps practices; monitor system performance and implement optimizations.
• Ensure products are compliant with internal security and risk policies and external regulatory requirements such as GxP, and that continuity plans are in place for business-critical products.
• Translate customer requests, competitive activities, and industry trends into product requirements understandable by product teams and developers.
• Consult on complex Level 3 support issues and escalations.
• Work with the broader team to deliver business value to tight timelines, adhering to the release management calendar where applicable, and work closely with data engineers, scientists, and business stakeholders.
• Act as a change agent, supporting product teams and the business in agile approaches to solution development and adoption.

What you'll need

• Minimum 10 years of hands-on technical experience in data engineering, AI/ML, and automation projects within regulated industries.
• Strong proficiency in Python.
• Hands-on experience designing and implementing RAG architectures, context enrichment strategies for LLM applications, and vector databases such as Azure AI Search Vector Capabilities.
• Experience with multi-agent orchestration frameworks such as LangChain, LangGraph and Semantic Kernel; knowledge graph integration.
• Experience with cloud-based data platforms like Snowflake and Azure, including development, integration, and configuration (Azure Data Factory, Azure Databricks, Azure App Services, Azure Cognitive Services, ADLSv2, Azure Key Vault and more).
• Experience with implementation of DevOps best practices (version control, CI/CD, Azure DevOps, YAML pipelines).
• Experience with data analytics platforms, data visualization or Business Intelligence tools (preferably Power BI).
• Experience with data virtualization (Denodo).
• Excellent problem-solving skills, a proactive mindset, and the ability to collaborate effectively across technical and business teams.
• Strong communication and interpersonal skills, with the ability to influence senior leadership and decision-making using data and market evidence.
• Good track record in delivering business impact through process and IT enabled solutions across multiple business lines.

Nice to have

• Experience of Drug Safety systems such as Argus, Aris-G or Veeva.
• Experience of other platforms such as Power BI, Azure, Snowflake.
• Python with PySpark and FastAPI.
• Understanding of data mesh / fabric principles.
• Understanding of data warehouse design and ELT processes.
• Experience in designing scalable architectures and automating business processes using AI.
• Knowledge of cloud and web service platforms such as Azure Databricks and RESTful web services.

Details

• Location: Bengaluru Luxor North Tower.