Data Engineer II

Role Summary

Data Engineer II within the Onyx Research Data Platform at GSK, focused on designing, delivering, and maintaining automated end-to-end data services and pipelines. Work across structured, unstructured, and scientific data domains to deliver reliable, scalable, and governed data products, with opportunities to contribute to GenAI-enabled data capabilities.

Responsibilities

• Build modular code / libraries / services using modern data engineering tools (Python/Spark, Kafka, Storm) and orchestration tools (e.g., Google Workflow, Airflow Composer)
• Produce well-engineered software, including automated test suites and technical documentation
• Develop, measure, and monitor key metrics for all tools and services, and iterate to improve them
• Ensure consistent application of platform abstractions for logging and data lineage
• Participate in code reviews and uphold coding best practices, improving the team's standards
• Adhere to QMS framework and CI/CD best practices
• Provide L3 support to existing tools / pipelines / services

Qualifications

• Required: Bachelor’s degree in Data Engineering, Computer Science, Software Engineering, or a related discipline
• Required: 4+ years of data engineering experience
• Required: Software engineering experience
• Required: Familiarity with orchestrating tooling
• Required: Cloud experience (GCP, Azure or AWS)
• Required: Experience in automated testing and design
• Preferred: New PhD or a Masters degree with 2+ years of experience
• Preferred: Experience overcoming high-volume, high-compute challenges
• Preferred: Knowledge and use of programming languages such as Python, Scala, Java, including toolchains for documentation, testing, and operations/observability
• Preferred: Strong experience with modern software development tools and practices (Git/GitHub, DevOps tools, metrics/monitoring)
• Preferred: Cloud experience (AWS, Google Cloud, Azure, Kubernetes)
• Preferred: Experience with CI/CD implementations using git and common stacks (e.g., Jenkins, CircleCI, GitLab, Azure DevOps)
• Preferred: Experience with agile software development environments using Jira and Confluence
• Preferred: Demonstrated experience with data engineering tools (e.g., Spark, Kafka, Storm)
• Preferred: Knowledge of data modeling, database concepts and SQL
• Preferred: Exposure to GenAI or ML data workflows (vector stores, embeddings, feature pipelines)

Skills

• Proficiency with Spark, Kafka, Storm and related data processing frameworks
• Experience with data orchestration and workflow tools (Airflow, Google Workflow, etc.)
• Strong software engineering practices: testing, documentation, version control, and observability
• Knowledge of data governance, logging, and data lineage
• Familiarity with GenAI-enabled data concepts and vectorized data flows