Staff Software Engineer, Lakeflow Pipelines DR

Posted 3 Days Ago
Be an Early Applicant
2 Locations
In-Office
192K-260K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
Design and implement distributed systems for cross-region replication and disaster recovery of Lakeflow pipelines. Responsibilities include ensuring consistency, idempotency, causal ordering, failover, failback, metadata reconciliation, observability, recovery simulation, and failure-injection testing. The role requires building reliable, production-quality solutions for streaming and batch data pipelines while contributing to a long-term technical vision.
Summary Generated by Built In

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.

Skills Required

  • 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
  • Passion for distributed systems, databases, storage systems, streaming systems, or reliability engineering
  • Ability to define and work toward a multi-year technical vision with incremental, production-quality deliverables
  • 8+ years of experience working on related systems
  • PhD or advanced research experience in databases, distributed systems, or storage

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
  • Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
  • Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.

Databricks Insights

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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