Job Description

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

This is a direct hire opportunity.

Summary:

We’re seeking a seasoned Senior Data Platform Engine er to design, build, and optimize scalable data solutions that power analytics, reporting, and AI/ML initiatives. This full‑time role is hands‑on, working with architects, analysts, and business stakeholders to ensure data systems are reliable, secure, and high‑performing.

Responsibilites:

• Build and maintain robust data pipelines (structured, semi‑structured, unstructured).
• Implement ETL workflows with Spark, Delta Lake, and cloud‑native tools.
• Support big data platforms (Databricks, Snowflake, GCP) in production.
• Troubleshoot and optimize SQL queries, Spark jobs, and workloads.
• Ensure governance, security, and compliance across data systems.
• Integrate workflows into CI/CD pipelines with Git, Jenkins, Terraform.
• Collaborate cross‑functionally to translate business needs into technical solutions.

Qualifications:

• 7+ years in data engineering with production pipeline experience.
• Expertise in Spark ecosystem, Databricks, Snowflake, GCP.
• Strong skills in PySpark, Python, SQL.
• Experience with RAG systems, semantic search, and LLM integration.
• Familiarity with Kafka, Pub/Sub, vector databases.
• Proven ability to optimize ETL jobs and troubleshoot production issues.
• Agile team experience and excellent communication skills.
• Certifications in Databricks, Snowflake, GCP, or Azure.
• Exposure to Airflow, BI tools (Power BI, Looker Studio).

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