Staff Software Engineer, Lakeflow Pipelines DR

Databricks
Mountain View +1 more
On-site

In the 12 months to 30 Jun 2026, Databricks filed 3339 H-1B positions titled "Software Engineer". Source: U.S. Department of Labor, LCA disclosure data. A record of filings already made, not a commitment to sponsor.

Who this role is best for

Best suited to distributed systems engineers with deep expertise in data pipeline resilience working in enterprise environments.

Best fit for

  • Candidates with 8+ years of experience in distributed systems and pipeline reliability engineering
    — “8+ years of experience working on related systems preferred”
  • Engineers with expertise in Java, Scala, C++, Go, or Python and a focus on mission-critical systems
    — “Strong software engineering skills in Java, Scala, C++, Go, Python, or a similar production language”

Things to consider

  • The role requires a focus on high-fidelity recovery simulations and formal reasoning about failure modes
    — “High-fidelity recovery simulations, game-day testing, and formal reasoning about failure modes”
  • Candidates must be prepared to work on systems that ensure no silent data loss or duplication
    — “safe recovery without silent data loss or duplication”

How to stand out

  • Highlight experience with distributed consistency and replication in mission-critical systems
    — “Understanding of consistency, transactions, idempotency, replication, checkpointing, and data lineage”
  • Demonstrate ability to define and execute long-term technical visions with production deliverables
    — “Ability to define and work toward a multi-year technical vision with incremental, production-quality deliverables”
  • Showcase expertise in handling pipeline dependencies and metadata reconciliation
    — “Deep clone, metadata reconciliation, observability, and failure-injection testing”
Pace · SteadyCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design and implement resilient systems
  • contribute to multi-year technical vision
Typical background
8+ years of experience in distributed systems

Skills & requirements

Required

Distributed SystemsJavaScalaGoPythonConsistencyTransactionsReplicationCheckpointingData Lineage

Preferred

Phd In Databases, Distributed Systems, Or Storage

Stack & domain

JavaScalaC++GoPythonDistributed SystemsDatabaseStorage SystemsStreaming SystemsReliability Engineering

About the role

Original posting from Databricks

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 USDAbout 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.

Source: Databricks careers

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