Principal Enterprise Data Architect

This is Cellares Cellares is the first Integrated Development and Manufacturing Organization (IDMO) and takes an Industry 4.0 approach to mass manufacturing the living drugs of the 21st century. The company is both developing and operating integrated technologies for cell therapy manufacturing to accelerate access to life-saving cell therapies. The company’s Cell Shuttle integrates all the technologies required for the entire manufacturing process in a flexible and high-throughput platform that delivers true walk-away, end-to-end automation. Cell Shuttles will be deployed in Cellares’ Smart Factories around the world to meet total patient demand for cell therapies at global scale. Partnering with Cellares enables academics, biotechs, and pharma companies to accelerate drug development and scale out manufacturing, lower process failure rates, lower manufacturing costs, and meet global patient demand. The company is headquartered in South San Francisco, California with its commercial-scale IDMO Smart Factory in Bridgewater, New Jersey. The company is backed by world-class investors and has raised over $355 million in financing. Leveling will be based on overall experience, education, and demonstration of knowledge throughout the interview process. country: US all locations: [South San Francisco, CA] commitment: Full Time department: Information Technology location: South San Francisco, CA team: IT Responsibilities: Architect and implement Databricks Lakehouse architecture Build end-to-end ETL/ELT pipelines Define canonical data models and scalable patterns Integrate SAP S/4HANA, Tulip MES, LabVantage LIMS, Salesforce, and engineering systems Align with API-first/event-driven architecture (MuleSoft / Workato) Define data glossary, lineage, and quality frameworks Implement Unity Catalog and governance aligned to GMP/21 CFR Part 11 Prepare datasets for analytics and AI/ML use cases Support structured and unstructured data processing Evaluate and implement BI tools (Sigma, Looker, Tableau) Enable self-service analytics with governance Build pipelines using Python, SQL, Spark Establish reusable frameworks Partner with engineering, manufacturing, quality, finance and software teams Translate business needs into data solutions Requirements: Bachelor’s or Master’s degree in Engineering, Life Sciences, Information Systems, or related field 10+ years in data architecture/data engineering Strong Databricks/Spark experience Experience building data platforms from scratch Integration with ERP/MES/LIMS/CRM systems Azure cloud experience Self-awareness, integrity, authenticity, and a growth/entrepreneurial mindset