Director, Data Engineering

Role Summary

The Director, Data Engineering will design, build, and optimize scalable data pipelines and infrastructure to support analytics, AI/ML initiatives, and omnichannel strategies for the U.S. Affiliate. This individual contributor role will ensure efficient, secure, and reliable ingestion, transformation, integration and storage of pharmaceutical data while overseeing vendor-delivered engineering work. The role will focus on building the technical foundation required to integrate data across multiple channels, ensuring data quality, compliance, and accessibility for analytics and reporting. Additionally, this individual will collaborate with cross-functional teams to deliver data solutions that generate actionable insights, support business objectives, and drive performance.

Responsibilities

• Design and build scalable ETL/ELT pipelines and workflows using Databricks and DBT to ingest, transform, and store oncology commercial data.
• Integrate data across multiple channels (e.g., digital platforms, CRM systems, and other commercial data sources) to support omnichannel strategies and analytics.
• Optimize data architecture to ensure efficiency, security, and scalability for analytics and AI/ML initiatives.
• Evaluate and incorporate new tools and technologies to enhance data engineering capabilities.
• Monitor and improve data quality while ensuring compliance with healthcare regulations (e.g., HIPAA) and pharmaceutical standards.
• Collaborate with cross-functional teams, including data scientists, marketing analytics, payer analytics, IT, and commercial stakeholders, to deliver actionable data solutions.
• Manage vendor-delivered data engineering projects, ensuring technical excellence, timely delivery, and alignment with business objectives.

Qualifications

• Required: A Bachelor's degree in a related field such as Computer Science or Data Engineering
• Required: A minimum of 10+ years of experience in data engineering roles, with a focus on building scalable data pipelines and infrastructure, and a strong understanding of ETL/ELT processes, data architecture, and data warehousing
• Required: Hands-on experience using Databricks and DBT for data workflows and architecture optimization, along with familiarity with cloud-based platforms (e.g., AWS, Azure, or GCP)
• Required: Understanding of Oncology specific and relevant pharmaceutical industry data sets, especially for the US
• Required: Prior experience managing internal teams and external vendor resources
• Required: Strong communication skills, with the ability to connect data and its insights within the team and with various stakeholders
• Required: Ability to work within large and complex organizations
• Required: Ability to adapt in a quickly changing environment
• Required: Adaptability to learn and integrate new tools and technologies into the existing tech stack
• Required: Learn about Oncology therapy area and company’s business needs to ensure analytical outputs meet business needs
• Preferred: A Master's degree in Computer Science, Data Engineering, Statistics, or a related field is preferred
• Preferred: Working knowledge of statistics, statistical modeling, or related concepts to support analytics initiatives
• Preferred: Working knowledge of AI/ML concepts and tools to support analytics initiatives
• Preferred: Having worked in a country organization or a start-up is a plus