Staff Software Engineer, Lakeflow Pipelines DR

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…