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Databricks Data Engineer Jobs in Fremont, CA (NOW HIRING)

BayRock Labs

Principal Data Engineer

Milpitas, CA · On-site

They are seeking a highly skilled Senior Data Engineer / Data Architect with extensive experience in Azure and Databricks to build large-scale data platforms and deliver high-quality data products in ...

Bayrock Labs

Principal Data Engineer

Milpitas, CA · On-site

$80 - $85/hr

As a leading product engineering firm based in Silicon Valley, we provide full-cycle product ... CI/CD for Databricks workloads Big Data & Processing Frameworks * Apache Spark with advanced ...

Databricks

Staff Data Scientist

San Francisco, CA · On-site +1

$260K/yr

P-57 At Databricks, we are obsessed with enabling data teams to solve the world\'s toughest ... Engineering) Pay Range Transparency Databricks is committed to fair and equitable compensation ...

Sigma Computing

Data Engineer

San Francisco, CA

$140K - $180K/yr

As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both ...

Rays Techsolutions Inc.

Senior Data Engineer

San Jose, CA · On-site

$124K - $168K/yr

Senior Data Engineer Location: San Jose, California, United States Experience: 8 10 Years Job ... Strong hands-on experience with Databricks , AWS , PySpark , Python , SQL , and Apache Airflow

Databricks

Staff Data Scientist

San Francisco, CA · On-site

$192K - $260K/yr

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems ... Engineering) Pay Range Transparency Databricks is committed to fair and equitable compensation ...

Marencor

AWS Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Role: AWS Data Engineer (Python, Dataiku) Location: SFO, CA - Hybrid Job Brief As an AWS Data ... This role requires leveraging AWS native technologies and Databricks for data transformations and ...

Dlapiper

Data Engineer

Palo Alto, CA

$134K - $161K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Dlapiper

Data Engineer

San Francisco, CA

$134K - $162K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Together. Summary The Data Engineer, Solutions & Data role designs, builds, and operates data ... Data pipeline tooling and cloud data services experience (Azure Data Factory, Azure Databricks ...

Sigma Computing

Data Engineer

San Francisco, CA · On-site

$140K - $180K/yr

  • Medical

  • Retirement

As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both ...

Sigma Computing

Data Engineer

San Francisco, CA · On-site

$140K - $180K/yr

  • Medical

  • Retirement

As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both ...

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Showing results 41-60

All JobsDatabricks Data Engineer JobsDatabricks Data Engineer Jobs in Fremont, CA

Databricks Data Engineer information

See Fremont, CA salary details

$48.7K

$142K

$194.3K

How much do databricks data engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for databricks data engineer in Fremont, CA is $141,996.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $150,500.00 per year, depending on experience, location, and employer.

What is a Databricks data engineer?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a Databricks data engineer do?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

What are the key skills and qualifications needed to thrive as a Databricks data engineer?

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

How much does a Databricks data engineer make?

A Databricks Data Engineer typically earns between $90,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with advanced skills in Spark, cloud platforms, and data pipeline development can earn higher salaries.

Is a Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and big data processing. Skills in Apache Spark, cloud environments, and data pipeline development are highly sought after, leading to strong job growth in this field.

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

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

What are popular job titles related to Databricks Data Engineer jobs in Fremont, CA?

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

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

The top searched job categories for Databricks Data Engineer jobs in Fremont, CA are:

What cities near Fremont, CA are hiring for Databricks Data Engineer jobs?

Cities near Fremont, CA with the most Databricks Data Engineer job openings:

Databricks Data Engineer jobs near you
Infographic showing various Databricks Data Engineer job openings in Fremont, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $141,996 per year, or $68.3 per hour.

Principal Data Engineer

BayRock Labs

Milpitas, CA • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
BayRock Labs is a leading product engineering firm based in Silicon Valley, pioneering innovative tech solutions for business transformation. They are seeking a highly skilled Senior Data Engineer / Data Architect with extensive experience in Azure and Databricks to build large-scale data platforms and deliver high-quality data products in cloud environments.
Responsibilities:
• Build large-scale data platforms and design enterprise-grade architectures.
• Deliver high-quality data products in cloud environments.
• Implement end-to-end development on Azure Databricks and Lakehouse architecture.
• Optimize performance and cluster management for Databricks workloads.
• Develop and maintain data pipelines using Apache Spark and PySpark.
• Design and deliver scalable data products and business-aligned semantic layers.
• Collaborate with cross-functional stakeholders and influence architecture decisions.
• Guide on data governance frameworks and cloud cost optimization strategies.
Qualifications:
Required:
• 5–10+ years of hands‑on experience in data engineering or data architecture
• Strong expertise in Azure + Databricks ecosystem
• Proven experience building scalable, secure, high‑performance data platforms
• Ability to lead design discussions, influence architecture decisions, and mentor teams
• Strong problem‑solving mindset and passion for modern data engineering
• ADLS Gen2, ADF, Synapse, Azure SQL, Key Vault, App Services
• Cloud‑native architecture design, scalability, and cost optimization
• Security & governance: RBAC, Managed Identity, Private Endpoints
• End‑to‑end development on Azure Databricks
• Lakehouse architecture implementation
• Delta Live Tables (DLT), Unity Catalog
• Performance tuning, cluster optimization
• CI/CD for Databricks workloads
• Apache Spark with advanced PySpark transformations
• Structured Streaming & batch data pipelines
• Delta Lake architecture & optimization
• Python for automation, data engineering, and orchestration
• PySpark for distributed data processing
• SQL for complex query optimization and analytics engineering
• Enterprise Data Warehouse (EDW) architecture
• Dimensional modeling (Star/Snowflake)
• Data Vault 2.0 modeling
• Metadata‑driven ingestion frameworks
• Change Data Capture (CDC) implementation
• Medallion architecture (Bronze/Silver/Gold)
• Data lineage, governance, cataloging
• Master Data Management (MDM)
• Design and delivery of scalable data products
• Business‑aligned semantic layer design
• KPI frameworks & enterprise reporting enablement
• Integration of ERP, SaaS, and operational systems
• Hybrid Lakehouse + EDW architectures
• CI/CD pipelines (Azure DevOps, GitHub Actions, Bitbucket)
• Infrastructure as Code (Terraform, ARM templates)
• Automated testing (unit, integration, data quality)
• Monitoring, logging, and observability
• Agile/Scrum delivery
• Principal‑level solution architecture design
• Cross‑functional stakeholder collaboration
• Technical roadmap planning and execution
• Guidance on data governance frameworks (GDPR, SOX)
• Cloud cost optimization strategies
• Migration from legacy EDWs (Teradata, Oracle, SQL Server) to Lakehouse
Company:
BayRock Labs provides AI consulting, product engineering, cloud, data, and enterprise app development services for startups and enterprises. Founded in , the company is headquartered in San Jose, California, US, , with a team of 1001-5000 employees. The company is currently Late Stage.

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