Synced from Greenhouse · Jul 1

Software Engineer

DatabricksMountain View, CaliforniaPosted Jul 1, 2026
Software EngineerStaff
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$235k–$295k
Compensation
867
Other open Databricks roles
Jul 1
Posted
Greenhouse
Applicant system
Job descriptionReq 7934466002

Job Title: Senior Staff Software Engineer - Enzyme 

Location: Mountain View, California

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P-1183

 

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

The Lakeflow Engineering team here at Databricks is responsible for the entirety of the ETL product line. This includes products such as Materialized Views, Structured Streaming, and Delta Live Tables. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers. 

We're seeking a dedicated technical leader to spearhead the Materialized Views engineering team. The team is responsible for building next generation Materialized View features for both ETL  workloads and for query acceleration.

As part of this team, you will be working in one or more of the following areas to design and implement these next gen systems that leapfrog state-of-the-art:

  • Incrementally maintaining materialized views
  • Query optimization
  • Resource management
  • Efficient storage structures 
  • Automatic physical data optimization

The Impact you will have:

  • Solve real business needs at large scale by applying your software engineering.
  • Deliver a highly scalable, available, and fault-tolerant architecture for materialized views
  • Low level systems debugging, performance measurement & optimization on large production clusters.
  • Build architecture design, influence product roadmap, and take ownership and responsibility over new projects.
  • Introduce tools to allow greater automation and operability of services.
  • Use your deep experience to help prevent and investigate production issues.
  • Plan and lead complicated technical projects that work with several teams within the company.

What We’re Looking For:

  • 15+ years industry experience building and supporting large-scale distributed systems.
  • A passion for database systems, storage systems, distributed systems, language design, or performance optimization
  • Experience working towards a multi-year vision with incremental deliverables
  • Motivated by delivering customer value and impact.
  • Strong foundation in algorithms and data structures and their real-world use cases.
  • Experience driving company initiatives towards customer satisfaction.
  • BS/MS/PhD in Computer Science or related majors, or equivalent experience.

 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

 

Local Pay Range
$235,000$295,000 USD

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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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