Strategic Overview
Staff Software Engineer, Lakeflow Pipelines DR at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as 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….
The role is listed for Mountain View, California / San Francisco, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- 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…
- 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.
- 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+…
Required Qualifications & Candidate Blueprint
- 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
Salary & Benefits
Published compensation: $192,000 – $260,000 USD
- Ability to define and work toward a multi-year technical vision with incremental, production-quality deliverables
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Staff level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly 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,… — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.