Back
Tier-1 employer and metro location with broad technical scope, but seniority reduces applicant density.
Role expects bioinformatics and R&D data experience, making cross-industry transitions difficult.
Explicit 20+ years plus deep mandatory technical and leadership skills creates strict shortlisting filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead and mentor a team of data engineers to build scalable, automated end-to-end data services and pipelines for GSK R&D.
Define and implement long-term data engineering strategy focused on data ingestion, streaming, transformation, metadata, vectorized pipelines, and AI/GenAI integration.
Ensure engineering standards, including testing, code reviews, CI/CD, compliance with Quality Management practices, and collaboration with bioinformatics and platform teams.
20+ years of strong data engineering and software engineering experience including handling high volume, high compute challenges.
Proficiency in at least one programming language such as Python, Scala, or Java; experience with big data tools like Spark, Kafka, Storm.
Cloud experience with AWS, Google Cloud, Azure, Kubernetes, plus infrastructure as code tools (Terraform).
Experience with CI/CD pipelines (e.g., Jenkins, CircleCI), agile environments (Jira, Confluence), automated testing, and DevOps methodologies.
A senior technical leader blending hands-on engineering with strategic vision in complex data ecosystems.
Experienced in coordinating cross-team collaboration across platform, bioinformatics and ML/GenAI groups for integrated data solutions.
A champion of engineering discipline and continuous improvement, with ability to drive standardized practices and innovation beyond current enterprise frameworks.