Sr. Data Architect

Location: Elk Grove, CA
Description:
Hybrid role 3X a week in office in Elk Grove, CA; no remote capabilities.

This is a direct hire opportunity.

Summary:

We're looking for a Senior Data Architect to lead the design and optimization of our Databricks Lakehouse platform on Google Cloud Platform. In this role, you'll guide a team of data engineers, own end-to-end data architecture, and build scalable pipelines that support analytics, reporting, and machine learning across the organization. This position requires deep Databricks expertise, strong leadership, and the ability to communicate data strategy to both technical and executive teams.

Responsibilities:

• Lead and mentor a high-performing data engineering team
• Own Databricks architecture, including Spark, Delta Lake, and Lakehouse design
• Implement Unity Catalog for governance, access control, and lineage
• Optimize SQL workloads, Spark jobs, and overall platform performance
• Build scalable pipelines for structured, semi-structured, and unstructured data
• Integrate Databricks workflows into CI/CD using Git and Dev Ops best practices
• Ensure strong data security, masking, encryption, and audit logging
• Partner with analysts, data scientists, and business leaders to deliver high-impact data solutions

Qualifications:

• 10+ years in data engineering or data architecture
• Deep hands-on experience with Databricks (Google Cloud Platform preferred), Spark, PySpark/Scala, and Delta Lake
• Strong cloud experience (Google Cloud Platform preferred; AWS/Azure acceptable)
• Experience with vector databases and embeddings for RAG/LLM retrieval
• Advanced SQL and data warehousing expertise
• Proven ability to optimize ETL jobs and cluster performance
• Strong background in data governance and security (Unity Catalog or similar)
• Leadership experience and excellent communication skills
• Agile team experience

Tech Stack:

• Databricks, Spark, Delta Lake, Unity Catalog, PySpark, Python, SQL, Google Cloud Platform Storage, Pub/Sub, vector databases, Git/Git Lab, Jenkins, Terraform (plus), JIRA, Confluence, Looker Studio, Power BI.
• Databricks Data Engineer certification; experience with Kafka, Pub/Sub, Airflow, and BI tools.

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Contact:

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