Associate Director, Data Engineering

Role Summary

This leadership role oversees the BI&T-GPS Data Engineering Team, ensuring that data is available for downstream consumption by analytics systems, processes and personnel. The Associate Director will be responsible for leading a team of BI&T-GPS data engineers in strategizing, building and operationalizing data pipelines, working in close partnership with other BI&T leaders and GPS stakeholders. This role requires a visionary leader who can shape strategy for how best to deliver data for downstream uses, manage a team of technologists, deliver impactful technology solutions in an operationally effective manner, and foster collaboration across global teams. This role is responsible for the extraction, loading, and technical transformation of data and works in close partnership with the Analytical Engineering team, which owns business context, semantic modeling, and consumption-ready data products. This role owns data quality and reliability across GPS data pipelines, ensuring trusted, production-ready data for downstream analytics and decision-making.

Responsibilities

• Define data engineering goals in partnership with GPS stakeholders and BI&T-GPS leadership. Cascade goals appropriately, monitor progress, and adjust strategy as needed.
• Lead the BI&T-GPS Data Engineering team with a visionary approach, taking full accountability for delivering cutting-edge data engineering programs that drive impactful technology solutions.
• Provide regular updates on technical progress to stakeholders and BI&T leaders.
• Provide periodic updates and technical demonstrations to the Head of GPS.
• Build and manage a high-performing Data Engineering team.
• Direct management of 2–4 technology professionals in the USA or Europe.
• Matrix leadership of other technology professionals from the worldwide BI&T-GPS Team.
• Indirectly manage and influence other technology professionals from the ~200-person global BI&T-GPS data and analytics teams, ensuring delivery of data engineering work in a manner that connects with other BI&T-GPS strategic projects.
• Lead planning, diversity efforts, and colleague development initiatives to sustain a robust talent pipeline.

Technology Strategy & Innovation

• Develop, manage, and deliver a forward-thinking technology roadmap for Data Engineering that leverages emerging technologies and innovative solutions to deliver compelling value.
• Actively partner with GPS stakeholders to ensure data art of the possible is central to the team's strategy and roadmap.
• Partner with BI&T teams and GPS stakeholders to experiment with emerging technologies such as AI, scaling viable solutions to deliver measurable business value in data engineering.
• Ensure adherence to technical best practices in SDLC and analytics output, including scalable solutions, code version control, documentation standards, and deployment.
• Ensure data engineering DevOps is closely integrated into the overall BI&T-GPS DevOps process.
• Evaluate new technologies and proactively recommend impactful innovations with high ROI for inclusion on the overall GPS technology roadmap.

Stakeholder Collaboration & Engagement

• Cultivate strong relationships with GPS business stakeholders, BI&T teams, and cross-functional colleagues across global locations, fostering a collaborative environment that drives visionary data engineering solutions.
• Enterprise mindset: Actively seek out ways to partner with other BI&T Teams and leverage existing technologies and solutions in the most effective way for data engineering.
• Ruthless prioritization: work closely with GPS and BI&T leadership to define data engineering priorities and deliver the most impactful solutions aligned with business objectives.

Qualifications

• Required: 10+ years of progressive experience in Information Technology, data analytics, or pharmaceutical/healthcare industries, with a proven track record of visionary leadership and innovation.
• Required: 5+ years in a leadership role managing teams or delivering IT or analytics programs.
• Required: Hands-on experience with SDLC methodologies, including DevOps, Agile, and Waterfall, in regulated environments.
• Required: Proven track record of managing complex projects, including resource allocation.
• Preferred: Experience with biopharma product development, manufacturing operations, supply chain, or quality controls.
• Technical Expertise: Significant experience with programming languages relevant to managing data pipelines (e.g., Python, Java, Scala).
• Technical Expertise: Experience with Databricks or similar platform; cloud computing environments and services, preferably AWS.
• Technical Expertise: Significant experience with ELT processes, with an emphasis on building high performance data layers (Data and Analytics Engineering).
• Technical Expertise: Experience with DevOps principles for CI/CD.
• Technical Expertise: Experience with data streaming technologies, such as Kafka.
• Technical Expertise: Proficiency with a modern suite of analytics tools and technologies, including GitHub, SQL, R, dbt, Domino, Tableau (Analytics Development).
• Technical Expertise: Experience with building and operationalizing predictive models, simulation, optimization frameworks and AI solutions is a plus (Analytics Ops).
• Technical Expertise: Experience with graph database technology is a plus.
• Technical Expertise: Hands-on experience with agile methodologies and tools like JIRA.
• Leadership Skills: Proven ability to lead technology teams or programs, foster collaboration, and drive innovation.
• Leadership Skills: Excellent project management skills, with a focus on delivering high-quality solutions on time and within budget.
• Leadership Skills: Strong communication skills to explain the business value of data engineering projects and operations.
• Leadership Skills: A customer-oriented mindset with an eagerness to solve business problems and drive continuous improvement.
• Leadership Skills: Ability to work effectively in a matrixed organization and across global locations.

Education

• Bachelor's degree in a quantitative or scientific discipline is required.
• Advanced degrees (MS or PhD) in relevant fields are preferred.

Additional Requirements

• Occasional travel to BMS locations throughout the world is anticipated.