Principal Data Engineer

Job description

Business Introduction GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centred on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems. Our diverse portfolio consists of vaccines, specialty medicines, and general medicines. Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges. Job Description Are you highly self-motivated, forward-thinking and like to explore new ways of applying existing new technologies to solve business problems? Do you understand the importance of prioritizing according to business value and can communicate with stakeholders? We’d like to hear from you if you think you might make a good fit! The distinct behavior demonstrated by a Principal Data Engineer is defined by Product Thought Leadership and Innovation. The Principal Data Engineer for Global Drug Safety, within GSK R&D Tech, is accountable for delivering solutions in line with the Drug Safety roadmap with a focus on improving efficiency whilst working collaboratively with peers and stakeholders. The role will have responsibility for leading design, development and delivery of various Drug Safety Data products within GSK’s Global Safety Operations and Safety Data product set and will have a key role in shaping and creating GSK’s future Drug Safety and data platforms. Experience of Drug Safety systems such as Argus / Aris-G / Veeva is desired, as is experience of other platforms like tools such as Power BI, Azure, Snowflake. As a Principal Data Engineer, you will contribute to the technical evolution of our data processing and automation capabilities. This role is focused on developing robust, scalable solutions that analyze our patient safety data far more effectively than current processes. You will leverage AI, machine learning, and advanced automation techniques to mitigate manual business processes and drive continuous improvement in data quality and efficiency. About R&D Tech, Data Acquisition & Management in Drug Safety Solutions GSK R&D is led by science. Science is driving an ever-increasing variance and complexity of Drug Safety, and its related data collection and management. This presents great opportunity for Tech enablement via investments in modern platform technologies and Digital applications, across GSKs Pharma and Vaccines organizations. In this role you will Technical Leadership & Architecture: Design and implement end-to-end, AI-driven data pipelines that ingest, transform, and analyze safety data from multiple sources. Lead to build enterprise data platforms with modern AI-Native solutions by leveraging technologies such as RAG, Vector Databases, Agentic AI, LLMOps, LangChain, LangGraph, Semantic Search, AI Agents, and Azure OpenAI to deliver intelligent, autonomous, and AI-driven business capabilities. Automation & Process Optimization: Build scalable solutions that replace labor-intensive tasks with automated workflows, significantly reducing processing time and errors. Collaborate with the Product Owner and cross-functional teams to ensure technical solutions align with the strategic product roadmap. Product/Project Delivery: Deliver the optimal set of products and services which meets the business strategy and requirements. Execution of the product roadmap. The ability to think big picture and customer first is imperative. Data Analysis & Enhancement: Develop novel approaches to extract actionable insights from complex data sets. Utilize advanced analytics techniques to continuously optimize data quality, drive signal detection, and support regulatory reporting. Operational Excellence: Ensure solutions adhere to best practices in software development, including robust testing, code documentation, and DevOps practices. Monitor system performance, proactively identify areas for improvement, and implement optimizations to maintain high system reliability. Quality, Risk & Compliance: Responsible for ensuring all products supporting the business are compliant with internal security, risk management policies and practices, external regulatory and statutory requirements e.g. GxP, and that Tech continuity plans are in place for all business-critical products. Feature Definition: Proven ability to translate customer requests, competitive activities, and industry trends into value drivers of new technology solutions and product requirements that can be easily understood by product teams, developers and other key constituencies within the organization. Service Management: Consult on complex Level 3 support issues and escalations. Team Collaboration: Work in collaboration with the broader team to drive and deliver business value to tight timelines adhering to the release management calendar where applicable. Work closely with data engineers, scientists, and business stakeholders to troubleshoot issues, gather requirements, and drive technical innovations. Adoption strategy & change management: In the role of change agent, support both the product teams and the business in agile approaches to solution development and adoption, building excitement, momentum, visible success stories and clear value-based versions of vision as roadmap plans come to life. Qualifications & Skills: Minimum 10 years of hands-on technical experience in data engineering, AI/ML, and automation projects within regulated industries Strong proficiency in programming languages such as Python (PySpark and Fastapi is a plus) Possess hands-on experience in the following AI-Native technologies: Designing and implementing RAG architectures, Context enrichment strategies for LLM applications, Vector Databases such as Azure AI Search Vector Capabilities, Multi-agent orchestration frameworks such as LangChain, LangGraph and Semantic Kernel; Knowledge graph integration. Experience with cloud-based data platforms like Snowflake and Azure - 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, ability to influence sr. leadership and decision-making using data, market evidence Good track record in delivering business impact through process and IT enabled solutions, across multiple business lines Preferred Qualifications & Skills: Understanding of data mesh / fabric principles Understanding Datawarehouse design and ELT processes Experience in designing scalable architectures and automating business processes using AI Knowledge of cloud & webservice platforms such as Azure Databricks, RESTful Webservices Relentless for delivering business outcomes and value and simplification with a passion for science and advancing medicines to patients . Skills Application Integrations, Application Programming Interface (API) Security, Azure Data Factory, CI/CD, Cloud Engineering, Configuration Management (CM), Database Management, Data Engineering, Data Integration, Data Mesh, Data Warehouse Design, Front-End Development, Internet of Things (IoT), Mobile Development, RESTful API Design, Scalable Architectures, Security System Design, Software Development Life Cycle (SDLC), Version