Data & AI Platform Engineer I, Commercialization

The Commercial Data & AI HYD team is seeking a Data & AI Platform Engineer I to help build and support the Databricks and Unity Catalog platform infrastructure underpinning the team's data products.

The successful candidate will support cloud engineering tasks for the platform, help maintain platform configuration in line with enterprise architecture standards, and assist with access controls, monitoring, and basic troubleshooting, working under the guidance of senior platform engineers on the team.

This is an early-career role that offers strong exposure to Databricks platform administration and cloud infrastructure practices, with a clear path to grow into progressively more senior platform engineering responsibilities over time.

Key Responsibilities:

• Support the configuration and operation of Databricks and Unity Catalog platform components, including workspace, cluster, and access configuration, under senior guidance.
• Assist with cloud engineering tasks for the platform, including basic provisioning and monitoring of underlying cloud infrastructure.
• Help coordinate with Enterprise IT on systems integration and feature enablement, supporting rollout of new platform capabilities to the team.
• Support platform reliability and security by helping implement access controls, monitoring, and configuration management for the Databricks environment.
• Assist in troubleshooting platform-level issues affecting pipeline execution, working with data engineers and senior platform engineers to isolate root causes.
• Support validation of newly migrated infrastructure against performance and reliability requirements before cutover to production use.
• Help document platform configuration, access patterns, and operational runbooks to support consistent operations across the team.
• Participate in code reviews and follow established engineering practices for version control and basic testing.
• Apply data governance and secure data handling practices, including access controls and protection of sensitive data.

Skills & Competencies:

• Working proficiency in SQL and Python for basic platform automation and configuration scripting.
• Exposure to Databricks platform administration (workspace configuration, clusters, jobs, Unity Catalog) and a foundational understanding of Delta Lake concepts.
• Basic understanding of cloud infrastructure fundamentals (e.g., AWS storage, compute, networking, and IAM concepts).
• Understanding of access control and security considerations for a shared data platform handling sensitive commercial pharma data.
• Familiarity with infrastructure-as-code or configuration management concepts.
• Working knowledge of Git/version control and a willingness to learn CI/CD practices.
• Good troubleshooting instincts and communication skills, with the ability to work effectively with data engineers and Enterprise IT.
• Understanding of data governance and secure data handling practices, including access controls and protection of sensitive data.

Qualifications & Experience:

• A bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
• 1-2 years of experience in platform engineering, cloud infrastructure, DevOps, or data platform administration, or a relevant internship or academic project background.
• Exposure to Databricks or a similar cloud data platform.
• Some exposure to cloud platforms (AWS preferred) supporting data engineering workloads.
• Preferred: exposure to coordinating with a central IT or platform team on integration standards.
• Preferred: interest in, or exposure to, commercial pharma datasets.

We hire for skills and capabilities, not just credentials - if this role excites you, but doesn't perfectly match your resume, we encourage you to apply anyway.