Staff Software Engineer, Lakeflow Pipelines DR
Databricks
Mountain View, CA · $192k–$260k a year · Posted September 11, 2026
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Where Mountain View, CA ranks
Where Mountain View, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for AI-skill jobs45% · of 100
- #1Best cities for AI-skill jobs in the West Coast45% · of 71
- #1Best cities for mid-career professionals in the West Coast68% · of 71
- #1Best all-round cities for mid-career professionals in the West Coast85 / 100 · of 39
- #1Best all-round cities for AI careers in the West Coast96 / 100 · of 39
- #2Best cities for finance pay after cost of living$161k · of 35
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
Pay compared with the market
This listing pays about $226,000 a year. Across 402 open staff software engineer listings that state pay, the middle half runs $223,500 to $272,500 and the median is $244,000. That is inside the middle half of those listings, 7% below the median.
Listed pay is what employers advertise, not what people are paid.
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How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
RDQ427R70
Our mission at Databricks is to radically simplify the data lifecycle with a unified Lakehouse platform for data engineering, analytics, and AI. The Lakehouse addresses major challenges in enterprise data platforms, including reliability, data staleness, operational complexity, total cost of ownership, and data lock-in. Learn more about the Lakehouse architecture.
Lakeflow is a critical part of this vision, helping customers build and operate streaming and batch ETL pipelines that power business-critical data products. As these workloads become increasingly mission-critical, customers need them to continue operating through infrastructure failures and cloud-region outages.
As a Staff Engineer on the part of the Lakeflow Disaster Recovery team, you will design and implement distributed systems that replicate and recover pipelines across regions. A pipeline is more than source code and output tables: it includes streaming checkpoints, source offsets, stateful operator state, table versions, transaction metadata, schedules, and dependencies across a dataflow graph. You will solve challenging problems involving consistency, idempotency, causal ordering, failover, failback, and safe recovery without silent data loss or duplication.
You will work in one or more of the following areas:
Cross-region replication and recovery for Lakeflow pipelines, streaming tables, and materialized views
Distributed consistency across pipeline dependencies, table versions, and transaction logs
Failover and failback workflows with conservative correctness guardrails
Deep clone, metadata reconciliation, observability, and failure-injection testing
High-fidelity recovery simulations, game-day testing, and formal reasoning about failure modes
What we look for:
A passion for distributed systems, databases, storage systems, streaming systems, or reliability engineering
Strong software engineering skills in Java, Scala, C++, Go, Python, or a similar production language
Understanding of consistency, transactions, idempotency, replication, checkpointing, and data lineage
Ability to define and work toward a multi-year technical vision with incremental, production-quality deliverables
8+ years of experience working on related systems preferred
Optional: PhD or advanced research experience in databases, distributed systems, or storage
This role offers the opportunity to build the foundations of resilient Lakehouse computing and help customers keep their data pipelines running when failure matters most.
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 $192,000 — $260,000 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.