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Staff Software Engineer (Data Platform)

Pay
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Work setting
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Employment
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What you’ll work on

Full posting
  • Design and run the company-wide metrics store and Data Intelligence Platform

  • Design the base ETL framework used by all company pipelines

  • Build CI/CD, pipeline test frameworks and infrastructure-as-code tooling

  • Create APIs and conventions for telemetry, debug, feature and audit event logs

  • Provide technical leadership on long-term vision and requirements for the product

From the employer’s posting
Design and run the Databricks metrics store
Design the base ETL framework used by all pipelines developed at the company.
This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
Establish conventions and create new APIs for telemetry, debug, feature and audit event log data
Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.

About Databricks

More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.

In the employer’s words · Read in context

Apply at Databricks

Posting record

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Open 7 monthsWe first saw this posting 213 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Apr 14, 2026213 days ago
Recorded sightings
441
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 213

Up longer than most. Similar jobs usually come down between day 6 and day 56.

Well past Databricks’s usual: its jobs come down by about day 63.

From 13,630 similar postings that came down, and 19 of Databricks’s. Coming down is not always a hire.

Databricks is hiring

29 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring has slowed
  • Its jobs tend to stay up a long time
  • 3% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Databricks
  • dbt
  • Kafka
  • Airflow
Where the posting names them
P-1348 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Staff Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product. The impact you will have:
The impact you will have: - Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance. - Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company.
- Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance. - Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company. - Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
- Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company. - Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling. - Design the base ETL framework used by all pipelines developed at the company.
- Design the base ETL framework used by all pipelines developed at the company. - Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product. - Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products.
- Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product. - Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products. - Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change.
- Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change. - Represent Databricks at academic and industrial conferences & events. What we look for:
- Passion for data infrastructure and for enabling others by making their data easier to access. About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits
Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion
Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance
- Experience building, shipping and operating reliable multi-geo data pipelines at scale. - Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools. - Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems.
- Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools. - Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems. - Excellent cross-functional and communication skills, consensus builder.

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Complete your application on databricks.com. The employer’s form will show what is required.

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

P-1348

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a Staff Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product.

The impact you will have:

  • Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance.
  • Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company.
  • Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
  • Design the base ETL framework used by all pipelines developed at the company.
  • Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.
  • Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products.
  • Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change.
  • Represent Databricks at academic and industrial conferences & events.

What we look for:

  • 12+ years of industry experience 
  • 4+ years of experience building large scale distributed systems
  • 5+ providing technical leadership on large projects similar to the ones described above - ETL frameworks, metrics stores, infrastructure management, data security.
  • Experience building, shipping and operating reliable multi-geo data pipelines at scale.
  • Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools.
  • Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems.
  • Excellent cross-functional and communication skills, consensus builder.
  • Passion for data infrastructure and for enabling others by making their data easier to access.

 

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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View original posting ↗

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Bengaluru, India

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