2 часа назад
Principal Enterprise Data Architect (Databricks)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Enterprise Data Architect (Databricks): Building and operationalizing a Databricks-powered enterprise data platform for scalable, GMP-compliant cell therapy manufacturing with an accent on lakehouse architecture, data integration, governance, and AI readiness. Focus on designing canonical data models, implementing Python/SQL/Spark pipelines, integrating ERP/MES/LIMS/CRM systems, and enabling governed analytics across the enterprise.
Location: South San Francisco, CA; on-site
Company
is building an Integrated Digital Manufacturing Operations platform for scalable, GMP-compliant cell therapy manufacturing.
What you will do
- Architect and implement the Databricks Lakehouse enterprise data platform.
- Build end-to-end ETL/ELT pipelines and reusable data engineering frameworks with Python, SQL, and Spark.
- Define canonical data models, data glossaries, lineage, quality frameworks, and governed self-service analytics.
- Integrate SAP S/4HANA, Tulip MES, LabVantage LIMS, Salesforce, and engineering systems using API-first and event-driven architecture.
- Implement Unity Catalog and data governance aligned with GMP and 21 CFR Part 11.
- Prepare structured and unstructured datasets for analytics and AI/ML use cases while partnering with engineering, manufacturing, quality, finance, and software teams.
Requirements
- Bachelor’s or Master’s degree in Engineering, Life Sciences, Information Systems, or a related field.
- 10+ years of experience in data architecture or data engineering.
- Strong Databricks and Spark experience, including building data platforms from scratch.
- Experience integrating ERP, MES, LIMS, CRM, and engineering systems.
- Azure cloud experience.
- Self-awareness, integrity, authenticity, and a growth-oriented entrepreneurial mindset.
Culture & Benefits
- Fast-paced, mission-driven startup-style environment.
- Highly hands-on individual contributor role with approximately 90% hands-on work.
- Opportunity to establish foundational data capabilities and support future scaling with the Global Capability Center.
Hiring process
- Leveling is based on overall experience, education, and demonstrated knowledge during the interview process.
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