ZipRecruiter

Log In

1

Manager Databricks Data Engineer Jobs in California

Mondo

Senior Databricks Data Engineer

Marina Del Rey, CA · On-site

$200K - $225K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Senior Databricks Data Engineer Location-Type: Onsite, Santa Monica, CA (office relocation to ... Private equity, credit, or alternative asset management industry experience. * Bachelor's degree in ...

Numentica LLC

Senior Databricks Data Engineer

Calabasas, CA · On-site

$120K - $145K/yr

Senior Data Engineer (AI & Databricks) Location: Las Vegas, NV / Calabasas, CA Work Model: Onsite (4 days/week) Employment Type: Full-Time Work Authorization: U.S. Citizens (USC) & Green Card Holders ...

Kanak Elite Services Inc

Data Engineer

Bay Point, CA · On-site

$125K - $151K/yr

Databricks Data Engineer Location: [Bay Area, CA] Duration : 12+ Months Need experience with ... Build and manage data workflows with Databricks Jobs, Notebooks, and Workflows * Optimize Spark ...

next page

Showing results 1-20

All JobsDatabricks Data Engineer JobsManager Databricks Data Engineer JobsManager Databricks Data Engineer Jobs in California

Manager Databricks Data Engineer information

What is the difference between Manager Databricks Data Engineer vs Data Engineer?

AspectManager Databricks Data EngineerData Engineer
Primary FocusTeam leadership, project management, strategic planningData pipeline development, data modeling, ETL processes
Required SkillsLeadership, Databricks platform knowledge, data architectureSQL, Spark, Python, cloud platforms
CertificationsDatabricks certifications, leadership credentialsDatabricks certifications, technical skills
Work EnvironmentManagement, cross-team collaboration, strategic oversightHands-on data processing, coding, pipeline implementation

The Manager Databricks Data Engineer oversees data engineering teams and manages projects on the Databricks platform, focusing on strategy and leadership. In contrast, a Data Engineer primarily handles technical tasks like building data pipelines and coding. Both roles require Databricks platform knowledge and relevant certifications, but the managerial role emphasizes leadership and project management, while the Data Engineer role is more technical and execution-focused.

How much does a Manager Databricks Data Engineer make?

A Manager Databricks Data Engineer typically earns between $120,000 and $160,000 annually, depending on experience, location, and company size. They often require strong skills in Spark, SQL, and cloud platforms like Azure or AWS, along with leadership responsibilities. Compensation may also include bonuses and stock options.

Is a Manager Databricks Data Engineer in demand?

Manager Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for advanced data processing skills. They typically require expertise in Spark, SQL, and cloud environments, making their roles critical in data-driven organizations seeking scalable analytics solutions.

What are the most commonly searched types of Databricks Data Engineer jobs in California?

The most popular types of Databricks Data Engineer jobs in California are:

What are popular job titles related to Manager Databricks Data Engineer jobs in California?

For Manager Databricks Data Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Manager Databricks Data Engineer jobs in California look for?

The top searched job categories for Manager Databricks Data Engineer jobs in California are:

What cities in California are hiring for Manager Databricks Data Engineer jobs?

Cities in California with the most Manager Databricks Data Engineer job openings:

Manager Databricks Data Engineer jobs near you

AWS Databricks Data Engineer

Tror AI for everyone

Los Angeles, CA • On-site

$123K - $148K/yr

Contractor

Re-posted 7 days ago

Job description

Job Title: AWS Databricks Data Engineer

Job Location: Los Angeles CA (Hybrid)

Hire type: FTE / CTH

Note: Only Locals to California

 

Job Description –

We are seeking a highly skilled AWS Data Engineer with strong expertise in SQL, Python, PySpark, Data Warehousing, and Cloud-based ETL to join our data engineering team. The ideal candidate will design, implement, and optimize large-scale data pipelines, ensuring scalability, reliability, and high performance. This role requires close collaboration with cross-functional teams and business stakeholders to deliver modern, efficient data solutions.

Key Responsibilities

1. Data Pipeline Development

  • Build and maintain scalable ETL/ELT pipelines using Databricks on AWS.
  • Leverage PySpark/Spark and SQL to transform and process large, complex datasets.
  • Integrate data from multiple sources including S3, relational/non-relational databases, and AWS-native services.

2. Collaboration & Analysis

  • Partner with downstream teams to prepare data for dashboards, analytics, and BI tools.
  • Work closely with business stakeholders to understand requirements and deliver tailored, high‑quality data solutions.

3. Performance & Optimization

  • Optimize Databricks workloads for cost, performance, and efficient compute utilization.
  • Monitor and troubleshoot pipelines to ensure reliability, accuracy, and SLA adherence.
  • Apply query optimization, Spark tuning, and shuffle minimization best practices when handling tens of millions of rows.

4. Governance & Security

  • Implement and manage data governance, access control, and security policies using Unity Catalog.
  • Ensure compliance with organizational and regulatory data‑handling standards.

5. Deployment & DevOps

  • Use Databricks Asset Bundles for deployment of jobs, notebooks, and configuration across environments.
  • Maintain effective version control of Databricks artifacts using GitLab or similar tools.
  • Use CI/CD pipelines to support automated deployments and environment setups.

Technical Skills (Required)

  • Strong expertise in Databricks (Delta Lake, Unity Catalog, Lakehouse Architecture, Table Triggers, Workflows, Delta Live Pipelines, Databricks Runtime, etc.).
  • Proven ability to implement robust PySpark solutions.
  • Hands‑on experience with Databricks Workflows & orchestration.
  • Solid knowledge of Medallion Architecture (Bronze/Silver/Gold).
  • Significant experience designing or rebuilding batch‑heavy data pipelines.
  • Strong background in query optimization, performance tuning, and Spark shuffle optimization.
  • Ability to handle and process tens of millions of records efficiently.
  • Familiarity with Genie enablement concepts (understanding required; deep experience optional).
  • Experience with CI/CD, environment setup, and Git-based development workflows.
  • Solid understanding of AWS cloud, including:
  • IAM
  • Networking fundamentals
  • Storage integration (S3, Glue Catalog, etc.)

Preferred Experience

  • Experience with Databricks Runtime configurations and advanced features.
  • Knowledge of streaming frameworks such as Spark Structured Streaming.
  • Experience developing real-time or near real-time data solutions.
  • Exposure to GitLab pipelines or similar CI/CD systems.

Certifications (Optional)

  • Databricks Certified Data Engineer Associate / Professional
  • AWS Data Engineer or AWS Solutions Architect certification

Thanks & Regards

Akhil

akhil@tror.ai