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Manager Databricks Data Engineer Jobs in Santa Clara, CA

Senior Data Engineer

San Jose, CA ยท On-site

$124K - $168K/yr

Senior Data Engineer Location: San Jose, California, United States Experience: 8 10 Years Job ... Design and maintain scalable ETL/ELT pipelines using Databricks and PySpark . * Build and manage ...

Sr. Manager, Engineering

Mountain View, CA ยท On-site

$228K - $314K/yr

P-1107 At Databricks, we are obsessed with enabling data teams to solve the world's toughest ... We are looking for a Senior Engineering Manager to lead foundational teams within Trust and Safety ...

Data Engineer

Palo Alto, CA

$134K - $161K/yr

... manage field mappings and transformations to support consistent downstream consumption. Data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Showing results 21-40

Manager Databricks Data Engineer information

See Santa Clara, CA salary details

$52.3K

$152.3K

$208.5K

How much do manager databricks data engineer jobs pay per year?

As of Aug 17, 2026, the average yearly pay for manager databricks data engineer in Santa Clara, CA is $152,344.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,500.00 and $161,500.00 per year, depending on experience, location, and employer.

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.

What are the most commonly searched types of Databricks Data Engineer jobs in Santa Clara, CA?

The most popular types of Databricks Data Engineer jobs in Santa Clara, CA are:

What are popular job titles related to Manager Databricks Data Engineer jobs in Santa Clara, CA?

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

What job categories do people searching Manager Databricks Data Engineer jobs in Santa Clara, CA look for?

The top searched job categories for Manager Databricks Data Engineer jobs in Santa Clara, CA are:

What cities near Santa Clara, CA are hiring for Manager Databricks Data Engineer jobs?

Cities near Santa Clara, CA with the most Manager Databricks Data Engineer job openings:

Infographic showing various Manager Databricks Data Engineer job openings in Santa Clara, CA as of August 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $152,344 per year, or $73.2 per hour.

Senior Data Engineer

Rays Techsolutions Inc.

San Jose, CA โ€ข On-site

$124K - $168K/yr

Other

Posted 17 days ago


Job description

Senior Data Engineer

Location: San Jose, California, United States
Experience: 8 10 Years

Job Summary

We are seeking a Senior Data Engineer with strong expertise in Databricks, AWS, PySpark, and Apache Airflow to build scalable data pipelines and modern data platforms that support analytics and business-critical applications.

Required Skills
  • 8 10 years of Data Engineering experience.
  • Strong hands-on experience with Databricks, AWS, PySpark, Python, SQL, and Apache Airflow.
  • Experience with Delta Lake, Lakehouse Architecture, ETL/ELT pipelines, and data modeling.
  • Knowledge of GenAI, analytics, Git, CI/CD, and cloud security best practices.
Responsibilities
  • Design and maintain scalable ETL/ELT pipelines using Databricks and PySpark.
  • Build and manage data workflows using Apache Airflow.
  • Develop and optimize data solutions on AWS (S3, Glue, Lambda, EMR, Redshift).
  • Ensure data quality, performance, security, and governance.
  • Collaborate with cross-functional teams to deliver reliable and scalable data solutions.
  • Mentor junior engineers and contribute to engineering best practices.