Skills this job asks for
ReconciliationTriageSQL
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 260 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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What Stripe paid sponsored hires in similar roles5 certified filings for “Data Analyst” (Data Scientists) in CA: $195k–$212k, median $195k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 260 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-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 Stripe paid sponsored hires in similar roles
- 5 certified filings for “Data Analyst” (Data Scientists) in CA: $195k–$212k, median $195k. Most were filed at wage level IV (60%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
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.
About the role
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies from the world's largest enterprises to the most ambitious startups use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.
About the team
As Stripe's user base and global footprint grows dramatically, we face uniquely complex operational challenges at the intersection of payments infrastructure, financial data integrity, and global scale. The Stripe Delivery Center (SDC) provides operational leverage across Stripe's portfolio supporting external users and internal teams with precision and speed.
What you’ll do
As a Technical Operations Analyst on the Payments team, you will own the reliability and accuracy of some of the world's most critical payment flows, a platform processing hundreds of billions of dollars annually. You will sit at the intersection of engineering, finance, and operations: triaging live payment failures, driving reconciliation accuracy, and partnering with financial institutions globally to resolve issues fast.
This is not a passive monitoring role. You will be expected to independently own investigations end-to-end, identify systemic issues before they escalate, and drive process improvements that scale with Stripe's growth.
Responsibilities
• Own reconciliation and payments-related investigations, ensuring accurate ledgering of funds and resolving discrepancies with banking partners swiftly and precisely.
• Proactively monitor payment performance across users and payment methods; triage degradation alerts, diagnose root causes, and communicate findings clearly to technical and non-technical stakeholders.
• Serve as the escalation point for complex support inquiries from Technical Account Managers, Product Support, and internal Stripe teams providing fast, well-reasoned resolutions.
• Interface directly with Stripe's global financial partners (card networks, banks, payment processors) to manage operational incidents and drive resolution.
• Validate the accuracy of Stripe's financial data through rigorous analysis and cross-functional collaboration with finance and infrastructure engineering teams.
• Identify process inefficiencies and lead automation initiatives to reduce manual workload and improve operational throughput at scale.
• Build and maintain high-quality SOPs, runbooks, and process documentation to ensure institutional knowledge is captured and transferable.
Who you are
We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.
Minimum requirements
• 3-7 years of experience in a technical operations, payments operations, or financial technology role.
• Advanced SQL proficiency - you write complex queries (joins, window functions, aggregations) independently and use them as a primary tool for investigation and root cause analysis.
• Deep understanding of end-to-end payment flows - including authorization, clearing, settlement, reconciliation, and exception handling across multiple payment methods and geographies.
• Demonstrated experience investigating and resolving high-severity operational incidents in a payments or financial systems environment with minimal oversight.
• Strong experience working with large-scale financial datasets - validating accuracy, identifying anomalies, and reconciling discrepancies across systems.
• Proven ab
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