About this role
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.
Job Description: The Manager of Analytics Engineering provides hands-on technical expertise to develop, deploy, and maintain both core data models and core data layer infrastructure. This role is ideal for someone who thrives on building robust, scalable, and well-documented data models and pipelines, while also enabling self-service analytics across the organization.
We are seeking a highly skilled Analytical Engineer to join our team. This role bridges the gap between data engineering and data analytics, focusing on data architecture, quality, and governance. The ideal candidate will have experience designing and maintaining dimensional data models (star/snowflake schemas), including fact and dimension table design, slowly changing dimensions (SCD), and conformed dimensions across multiple subject areas.
This role requires strong technical expertise in data transformation, modeling, and pipeline optimization. Additionally, a successful candidate is an excellent communicator who can effectively explain complex technical information to a wide variety of stakeholders.
Key Responsibilities and Major Duties
Collaborate with the business to gather requirements and deliver data-products to enable data-informed decision-making.
Develop a centralized data-layer to deliver data-products at scale to the business.
Incorporating domain-specific data marts into a centralized, foundational core.
Harmonize data across manufacturing sites, software, and platforms for enterprise-level consumption.
Designing highly organized and scalable architectural solutions to drive efficiency.
Define orchestration strategies across multiple data domains.
Work within a governed metadata framework where documentation is a delivery requirement.
Work within Data Build Tool (dbt) to deliver documented, tested, and DRY (“don’t-repeat-yourself”) code.
Follow analytical lifecycle process and quality frameworks to deliver accurate data to internal consumers on-time.
Focus on innovative solutions to increase speed-to-delivery and accelerate business decision-making.
Qualifications/Degree/Certification/Licensure
BA/BS or higher required in Computer Science, Physics, Math, Data Science, Pharmaceutical Science, or Engineering area of study
Requires 4-6 yrs of relevant work experience.
Proficiency with SQL
Experience scripting (e.g. Python/R)
Working knowledge of DAG-based and asset-based pipeline design
Experience with version control (e.g. Git, SVN) and Agile development
Proven analytical and problem-solving ability
Experience working in or alongside agile/scrum teams highly desired
Expertise gathering requirements to understand business needs and define technical solutions
Excellent communications and presentation skills. Ability to explain complex analyses and outcomes to both technical and non-technical stakeholders
Hands-on experience with dbt a plus
Familiarity with our toolkit desired: work information process tools (JIRA, Confluence, ServiceNow, MS suites); data-related tools (Databricks, DBT)
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.
Compensation Overview
New Brunswick - NJ - US: $116,450 - $141,110