Data Team Lead

Databricks Data Lead

location:
San Rafael, CA - Bay Area, California (Local candidates only)

hybrid: 3 days/week onsite at client office in San Rafael, CA

• 8-12 years in data engineering, analytics engineering, or distributed data systems

We are seeking a Databricks Data Lead to support the design, implementation, and optimization of cloud-native data platforms built on the Databricks Lakehouse Architecture
. This is a hands‑on, engineering‑driven role requiring deep experience with Apache Spark, Delta Lake, and scalable data pipeline development
, combined with early-stage architectural responsibilities.

The role involves close onsite collaboration with client stakeholders, translating analytical and operational requirements into robust, high‑performance data architectures
, while adhering to best practices for data modeling, governance, reliability, and cost efficiency.

• Design, develop, and maintain batch and near‑real‑time data pipelines using Databricks, PySpark, and Spark SQL
• Implement medallion (Bronze/Silver/Gold) lakehouse architectures
  , ensuring proper data quality, lineage, and transformation logic across layers
• Build and manage Delta Lake tables
  , including schema evolution, ACID transactions, time travel, and optimized data layouts
• Apply performance optimization techniques such as partitioning strategies, Z‑Ordering, caching, broadcast joins, and Spark execution tuning
• Support dimensional and analytical data modeling for downstream consumption by BI tools and analytics applications
• Assist in defining data ingestion patterns (batch, incremental loads, CDC, and streaming where applicable)
• Troubleshoot and resolve pipeline failures, data quality issues, and Spark job performance bottlenecks
• Collaborate onsite with client data engineers, analysts, and business stakeholders to gather technical requirements, validate implementation approaches, and maintain technical documentation covering data flows, transformation logic, table designs, and architectural decisions
• Contribute to code reviews, CI/CD practices, and version control workflows to ensure maintainable and production‑grade solutions

• Strong hands‑on experience with Databricks Lakehouse Platform
• Deep working knowledge of Apache Spark internals
  , including:
  • Spark SQL
  • Data Frames/Datasets
  • Shuffle behavior and execution plans
• Advanced Python (PySpark) and SQL development skills
• Solid understanding of data warehousing concepts
  , including:
  • Star and snowflake schemas
  • Analytical vs operational workloads
• Experience working with cloud data platforms on AWS, Azure, or GCP
• Practical experience with Delta Lake
  , including:
  • Schema enforcement and evolution
  • Data compaction and optimization
• Proficiency with Git‑based version control and collaborative development workflows
• Strong verbal and written communication skills for client‑facing technical discussions
• Ability and willingness to work onsite 3 days/week in San Rafael, CA

• Exposure to Databricks Unity Catalog
  , data governance, and access control models
• Experience with Databricks Workflows
  , Apache Airflow
  , or Azure Data Factory for orchestration
• Familiarity with streaming frameworks (Spark Structured Streaming, Kafka) and/or CDC patterns
• Understanding of data quality frameworks, validation checks, and observability concepts
• Experience integrating Databricks with BI tools such as Power BI, Tableau, or Looker
• Awareness of cost optimization strategies in cloud‑based data platforms

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience)

• Hands‑on ownership of Databricks Lakehouse implementations in a real‑world enterprise environment
• Direct client‑facing exposure with a leading Bay Area organization
• Opportunity to evolve from senior data engineering into formal data architecture responsibilities
• Strong growth path toward Senior Databricks Architect / Lead Data Platform Engineer

• Mid‑Senior level

• Full‑time

• Consulting

• IT Services and IT Consulting
• Hospitals and Health Care
• Biotechnology Research

• Medical insurance
• Vision insurance
• 401(k)