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

Data Engineer

Pleasanton, CA · On-site

$127K - $152K/yr

Job#: 3044330 Apex Systems is hiring a Data Engineer with Databricks experience for a large Healthcare client. Location: Fully remote anywhere in the US. Role Overview We are seeking a Data Engineer ...

Databricks Engineer

Milpitas, CA · On-site

$120 - $180/hr

Integrate data from various sources including relational databases, APIs, cloud storage, and streaming platforms. * Optimize Spark jobs for performance, scalability, and cost efficiency.

New

Databricks Engineer Experience 4-8 years Location As per business requirement Employment Type ... Integrate data from various sources including relational databases, APIs, cloud storage, and ...

Databricks is looking for a Principal Data Scientist to serve as the statistical voice of the Data ... Partner with engineering VPs, product leaders, and executive staff to embed a data-driven decision ...

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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:

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.

Sr. Manager, Developer Relations - Databricks

Databricks

San Francisco, CA • On-site

Full-time

Posted 4 days ago


Job description

RDQ427R539

At Databricks, we are passionate about enabling data teams to solve the world's most challenging problems - from making the next mode of transportation a reality to accelerating medical breakthroughs. We do this by building and running the world's best data and AI platform, enabling our customers to use deep data insights to improve their businesses. Our ability to execute this mission depends on building trust and recognition within an ever-growing community of data engineers, analysts, scientists, machine learning practitioners, and AI practitioners.
Databricks' Developer Relations team is looking for a leader to manage our Developer Advocates, shape how we bring the Data + AI Platform to life, and lead technical content and experiences that drive product adoption. This role is ideal for someone who thrives in the spotlight, brings deep Databricks expertise, and gets even more satisfaction from helping other advocates grow into it.

As the Developer Advocate Manager for Databricks, you'll lead the team that advocates for our commercial platform and serve as a crucial link between our engineering teams and the broad community of data professionals building their careers on Databricks. Your team's remit spans the full arc of what practitioners actually do on the platform: ingesting and moving data with Lakeflow, building and governing pipelines and tables with Unity Catalog and Delta Lake, warehousing and analytics with Databricks Lakehouse and AI/BI, and building agents and AI applications with Genie Agent, Genie Code, Lakebase, and Databricks Apps. You'll be as comfortable talking to a data engineer debugging a pipeline as to an analyst building their first AI/BI dashboard and Genie One.

This role will leverage your expertise in building and scaling a developer relations team to educate, inspire, and support a rapidly growing user base. You'll translate product roadmaps into developer-ready content and community programs, and coach your team on building a content flywheel - where a single demo, video, or talk becomes the source of truth for a dozen derivative assets rather than a one-off deliverable. You'll also help the team apply AI thoughtfully as a force multiplier across their workflows, raising output without ever lowering the technical bar.

Your responsibilities will encompass both team leadership and a wide range of knowledge-sharing activities. You'll lead by example: delivering engaging talks, hosting panels and meetups, creating blogs and video content, developing courseware, answering questions in community forums, and meeting one-on-one with influential data engineers, analysts, and scientists.

Community engagement will be at the heart of your role. You'll work closely with the Databricks community and with product and engineering teams, ensuring that user needs and product development align seamlessly. Reporting directly to the Head of Developer Relations, you'll collaborate with fellow DevRel managers across our Open Source, App Dev, and DevRel Programs teams to create a cohesive and impactful developer relations strategy.

The ideal candidate embodies the values of our Developer Relations team: a deep passion for data and AI, genuine empathy for developers' needs, and a strong commitment to explaining our products clearly and honestly.

More about the DevRel team

The Developer Relations (DevRel) team at Databricks is dedicated to building and fostering relationships with communities of data practitioners. Our goal is to drive awareness and adoption of the Databricks Data + AI Platform - including Lakeflow, Lakebase, Genie Agent, and AI/BI - alongside the open source projects that underpin it, such as Apache Spark, Delta Lake, Unity Catalog, MLflow, Apache Iceberg, and Omnigent. Our team also owns programs like the Databricks MVP program, the user group program, and DevConnect roadshows.

The impact you will have
  • Own developer relations for the Databricks Platform end-to-end - set the strategy, define what success looks like, and be accountable for the outcomes.
  • Hire, level, and grow a team of Developer Advocates, and take real ownership of their careers: clear expectations, honest feedback, and a visible path forward.
  • Establish repeatable advocacy approaches - content flywheels, demo standards, event playbooks - that the rest of DevRel can adopt and replicate.
  • Build a team of strong storytellers who can make a complex platform feel obvious, and who scale their work through the community rather than through sheer volume.
  • Represent the practitioner community inside R&D at the product-area level, turning community friction into a documented, prioritized roadmap change.
  • Drive awareness and adoption of Databricks technologies through your own speaking at industry events and conferences, and by getting your team on the right stages.
  • Guide the creation of high-quality educational content - videos, sample notebooks, datasets, tutorials, courseware, and blog posts - that meets a high technical bar.
  • Expand and nurture the Databricks community by growing meetups and user groups and supporting practitioners in online communities.
  • Apply AI-assisted workflows to increase your team's leverage while maintaining technical depth and originality.
  • Define and defend meaningful success metrics for a DevRel team, and explain them to executives.
What we look for
  • 8+ years of combined experience in developer relations or developer advocacy and in a hands-on technical role - software engineer, data engineer, solutions architect, or similar.
  • 2+ years managing and growing a developer relations team, including hiring, leveling, and promoting advocates.
  • You have done the work yourself. You've written the posts, built the demos, given the talks, and sat in the forums - and you can still do all of it.
  • Demonstrated ability to set and execute a developer relations strategy for a product area, not just run a content calendar.
  • Subject matter knowledge of solving data engineering, data science, and data analytics problems at scale, and an understanding of how business users consume the results.
  • Comprehensive understanding of the Databricks Data + AI Platform and ecosystem - you can give the demo and use the product the way a practitioner would.
  • Working knowledge of Databricks capabilities such as Lakeflow, Unity Catalog, Delta Lake, Databricks Lakehouse, AI/BI Dashboards, Genie, Genie Agents, and Databricks Apps.
  • A genuine passion for growing people and building strong teams.
  • Active participation and recognized leadership in data and AI community forums, chats, and meetups.
  • Proven track record in nurturing developer communities, organizing user groups, and facilitating global meetups.
  • Exceptional communication skills, with a talent for articulating complex concepts through writing, teaching, video, and public speaking.
  • Deep empathy for developer needs, with the ability to craft engaging experiences across tutorials, notebooks, and community platforms.
  • Experience using AI to scale a team's output without lowering the technical bar.
  • Adept at collaborating with cross-functional stakeholders to align community initiatives with product objectives.