Job Description

Job Title 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

Experience Level

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

Role Overview

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 .

Key Responsibilities

• 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
• Review architecture designs
• Validate implementation approaches
• 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

Required Skills & Qualifications

• Strong hands-on experience with Databricks Lakehouse Platform
• Deep working knowledge of Apache Spark internals , including:
• Spark SQL
• DataFrames/Datasets
• Shuffle behavior and execution plans
• Advanced Python (PySpark) and SQL development skills
• Solid understanding of data warehousing concepts , including:
• Star and snowflake schemas
• Fact/dimension modeling
• Analytical vs operational workloads
• Experience working with cloud data platforms on AWS, Azure, or GCP
• Practical experience with Delta Lake , including:
• Merge/upsert patterns
• 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

Nice-to-Have Skills

• 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
• Prior Lifesciences Domain Experience

Education

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

Why This Role

• 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

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