Jobs / United States / Databricks
Staff Software Engineer - Streaming
Databricks · 🇺🇸 Bellevue, Washington; Seattle, Washington
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 445 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 78 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Databricks paid sponsored hires in similar roles50 certified filings for “Software Engineer” (Software Developers) in WA: $149k–$190k, median $163k. Most were filed at wage level II (42%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Databricks
The US Department of Labor certified 445 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 78 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Databricks →
About the role
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can turn deep data insights into better business outcomes. We are the Spark Structured Streaming team, responsible for building stream processing into Apache Spark and the Databricks Data Intelligence Platform. Stream processing is still in its early days, and we're here to build not only state-of-the-art streaming technology but also a best-in-class managed offering for customers to run their streaming workloads. The role We're seeking an experienced Staff Engineer to drive the technical direction of Spark Structured Streaming, spanning both open source and Databricks-specific components. Your mission is to make Spark Structured Streaming the state-of-the-art stream processing engine — adding advanced capabilities such as sophisticated state management and new operators, while re-imagining the engine's architecture to drive improvements for latency, throughput, and cost. What you'll do: • Set and drive the technical vision for Spark Structured Streaming across OSS and the Databricks Data Intelligence Platform • Design and build core engine capabilities — state management, new operators, and architectural improvements to latency and throughput • Raise the bar for engineering quality and operability, building software that is not just high quality but easy to run in production • Make company-wide impact by driving stream processing adoption across the Databricks product portfolio • Guide long-term architecture and technical-debt decisions, balancing them against the product roadmap • Mentor and technically lead engineers on the team, and partner with the Engineering Manager to attract and grow top-tier talent What we look for: • BS (or higher) in Computer Science or a related technical field, or equivalent practical experience • 8+ years building related systems — big-data ecosystems, Apache Spark, or database internals • A passion for database systems, storage systems, distributed systems, language design, or performance optimization • Comfortable working toward a multi-year vision with incremental deliverables • A track record of delivering features while maintaining a high bar for operational excellence and engineering quality • Comfortable working cross-functionally with product management and directly with customers, with the ability to deeply understand the product and customer personas 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 $182,400 — $247,000 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, anal