Senior Data Engineer
Numentica•San Diego, CA
About The Position
We are seeking a hands-on Technical Lead to lead the development and operation of its Microsoft Fabric-based Platform. This role combines data platform architecture, hands-on engineering, technical leadership, and business partnership.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field.
- 7–10 years of experience in data engineering, data platforms, or analytics infrastructure.
- 2+ years of technical leadership experience with data/analytics engineers.
- Strong hands-on experience with Microsoft Fabric; Databricks or Azure Synapse experience may be considered.
- Strong proficiency in PySpark, Python, T-SQL, ETL/ELT, and modern data engineering practices.
- Experience with medallion/layered data architecture at enterprise scale.
- Experience with DevOps, CI/CD, Azure DevOps/GitHub, and infrastructure-as-code.
- Knowledge of data governance and quality frameworks such as Microsoft Purview.
- Experience managing technical delivery from external vendors.
Nice To Haves
- Biopharma, life sciences, or other regulated-industry experience, including GxP and validation requirements.
- Experience with Veeva, LIMS, ELN/Benchling, CTMS, EDC, MasterControl, or HRIS integrations.
- Experience with AI/ML workloads on a lake-house.
- Microsoft Fabric Data Engineering certification.
Responsibilities
- Lead the architecture and engineering of the Microsoft Fabric data lake-house, including OneLake, medallion architecture, Spark/SQL, and CI/CD.
- Provide hands-on technical leadership, mentoring, code reviews, and architectural guidance to data and analytics engineers.
- Design and build scalable data pipelines integrating 50+ enterprise source systems.
- Partner with business stakeholders across R&D, Commercial, Manufacturing, Supply Chain, and Corporate functions to translate business needs into data solutions.
- Manage and technically oversee external implementation partners, ensuring engineering quality and adherence to standards.
- Establish platform support models, SLAs, monitoring, data quality, incident management, and operational processes.
- Define and track platform KPIs such as pipeline reliability, data freshness, query performance, onboarding velocity, and incident resolution.
- Develop the semantic layer, including Power BI datasets, gold-layer views, and self-service analytics.
- Implement data governance, security, classification, RBAC, sensitivity labeling, and audit requirements.
- Establish engineering standards for development, testing, branching, documentation, and deployment.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
