Data Engineer I, Commercialization

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it. Position Summary The Commercial Data & AI HYD team is seeking a Data Engineer I to support the foundational data pipelines that bring raw commercial data into the Databricks Lakehouse. The successful candidate will help build bronze and silver layer pipelines, support the promotion of datasets through a staged progression of testing, validation, and production environments, and assist with onboarding new data sources and vendors, applying scripted and rules-based approaches under the guidance of senior engineers on the team. This is an early-career role that offers strong exposure to Databricks-based data engineering and data architecture practices, with a clear path to grow into progressively more senior data engineering responsibilities over time. Key Responsibilities * Help build bronze and silver layer pipelines that ingest, cleanse, and prepare raw source data for downstream consumption, under the guidance of senior engineers. * Support the promotion of new and existing datasets through a staged progression of testing, validation, and production environments, helping verify each dataset is properly vetted before release. * Support the onboarding of new data sources and vendors by helping set up initial testing environments and checking data quality and business rules, escalating gaps to senior engineers. * Monitor metadata, integration, and data warehouse/lakehouse architecture for assigned data pipelines, under the guidance of senior engineers. * Create documentation and visual representations of end-to-end data architecture for assigned pipelines. * Follow established data migration plans and help monitor for potential impacts during migration. * Provide input into data dictionaries for assigned data domains. * Build basic monitoring and data quality checks for assigned pipelines, using scripted and rules-based approaches. * Support troubleshooting of production pipeline issues and assist with root cause analysis under senior guidance. * Apply data governance and information security practices for sensitive and regulated data, including PII/PHI awareness. Skills & Competencies * Working proficiency in SQL and Python (or a similar scripting language) for building basic automation and monitoring scripts. * Exposure to Databricks (notebooks, jobs, workflows) and a foundational understanding of Delta Lake concepts. * Exposure to working across a staged environment model (testing through validation to production) for releasing new or updated datasets. * Interest in, or exposure to, onboarding new data sources or vendors, including basic data quality checks. * Familiarity with data architecture documentation and metadata management concepts. * Basic understanding of data migration planning and impact monitoring. * Familiarity with ETL/ELT pipelines and lakehouse concepts (medallion architecture). * Basic understanding of cloud data storage fundamentals (e.g., AWS storage and compute). * Working knowledge of Git/version control and a willingness to learn CI/CD practices. * Understanding of data governance and information security practices, including documentation and access controls. 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 data engineering, or a relevant internship or academic project background. * Exposure to SQL and Python for data ingestion, transformation, or validation. * Some hands-on experience with Databricks (notebooks, jobs/workflows) or a similar cloud data platform. * Preferred: exposure to onboarding a new data source or validating data quality for a new source system. * Preferred: exposure to data architecture documentation or metadata management. * 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. How We Work Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working. Supporting People with Disabilities BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement. Candidate Rights BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. 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