Associate Director, Hypercell, Data Engineer

Senior Data Engineer

The Hypercell team is focused on transforming cell therapy operations by streamlining supporting processes through digital, automation, and AI-driven solutions. We are seeking a Senior Data Engineer to architect and implement scalable data infrastructure that enables advanced analytics, automated reporting, and AI-powered decision-making across the cell therapy network.

This role will work closely with Business Insights & Technology (BI&T) and cross-functional stakeholders to build robust data hierarchies, integrate diverse data sources, and support the deployment of innovative tools that improve operational efficiency and transparency.

Key responsibilities include:

• Design, build, and maintain scalable data pipelines and data models to support Hypercell's digital and AI initiatives.
• Collaborate with BI&T and process engineering teams to define and implement data hierarchies that enable automated report generation from source systems.
• Integrate structured and unstructured data from manufacturing, quality, and digital platforms into unified, accessible formats.
• Support the development and deployment of AI-facing tools, ensuring data readiness, integrity, and traceability.
• Partner with data scientists and engineers to enable advanced analytics, predictive modeling, and process optimization.
• Ensure data governance, security, and compliance with internal and external regulatory requirements.
• Troubleshoot data-related issues and implement solutions to improve data reliability and performance.
• Contribute to the development of dashboards, visualizations, and self-service tools for end users across the business.

Qualifications and experience required:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
• 7-10+ years of experience in data engineering, preferably in biopharma, cell therapy, or regulated manufacturing environments.
• Strong proficiency in SQL, Python, and data pipeline frameworks (e.g., Apache Airflow, DBT).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and data warehousing solutions (e.g., Snowflake, Redshift).
• Familiarity with GMP data requirements and regulatory expectations for data integrity.
• Proven ability to work cross-functionally and translate business needs into technical solutions.

Preferred qualifications:

• Experience supporting AI/ML initiatives through data engineering and model deployment.
• Knowledge of manufacturing systems (e.g., MES, LIMS, ERP) and integration strategies.
• Familiarity with visualization tools (e.g., Power BI, Tableau) and self-service analytics platforms.
• Strong communication skills.