Business Intelligence Analyst

Block•Bay Area, CA, United States of America, CA

2d•$108,200 - $202,800•Remote

About The Position

You will join the Recon and Reporting team, which owns our post-transaction systems: the platform responsible for reconciling money, tracing the end-to-end flow of funds, and meeting our tax and regulatory reporting obligations to merchants, customers, and authorities worldwide. Reconciliation and financial reporting are essential to running a payments business, and given our transaction volume, this role has direct, measurable impact on financial accuracy and trust. As a Senior Analyst on the team, you will independently own reconciliation and reporting workstreams end to end. You will be the subject matter expert who ensures the numbers tie out: reconciling card-network settlement and report files (Visa, Mastercard, and equivalents), along with data from acquirers, processors, and banks, against our internal payment and ledger data. You will translate ambiguous reconciliation and reporting needs into concrete metrics, controls, and automated solutions, drive discrepancies to root cause and resolution, and directly influence the team's roadmap and the priorities of our finance, accounting, and engineering partners. Our mantra: all funds in the right place, at the right time, for the right purpose.

Requirements

5+ years of related experience in reconciliation, settlement, payment operations, accounting, or finance analytics with a Bachelor's degree (Finance, Accounting, Economics, a quantitative field, or similar); or 3+ years with a Master's degree; or equivalent work experience.
Expert-level SQL, including owning the design, development, and documentation of automated SQL-based reporting, and the ability to navigate new datasets and answer complex questions independently.
Demonstrated experience independently owning reconciliation, settlement, or financial reporting workstreams end to end, including defining metrics and driving them to adoption.
Strong knowledge of accounting principles, double-entry concepts, and the mechanics of money movement, with the judgment to question the correctness and completeness of financial data.
Experience partnering with data engineering (or working independently) to design, build, validate, and maintain data pipelines, with the ability to make sound technical trade-offs.
Advanced Excel proficiency (complex formulas, pivot tables) and experience with reconciliation tooling and banking portals.
Excellent communication skills: able to own senior stakeholder relationships, present findings and recommendations, and drive clear next steps in areas without clear ownership.
Track record of proactively identifying and delivering process improvements and automation in a deadline-driven, high-accuracy environment.

Nice To Haves

Deep experience with card-network reconciliation and settlement (Visa, Mastercard, Amex, Discover), including network settlement, clearing, and report file formats.
Strong familiarity with funds-transfer processes and rails (ACH, wire, SWIFT, RTP/FedNow) and the payments ecosystem: merchants, acquirers, issuers, processors, and program banks.
Scripting skills (Python or similar) for data analysis and process automation.
Experience with cloud data warehouses (e.g., Snowflake, BigQuery) and BI platforms (e.g., Looker, Tableau), including building governed reporting layers with SLAs.
Exposure to interchange and fee/cost reconciliation, revenue-leakage detection, and tax or regulatory reporting regimes.
Experience supporting audits, internal controls, or SOX-adjacent processes, and mentoring junior analysts.
Curiosity about payments products and financial markets.

Responsibilities

Independently prioritize, design, develop, and deploy end-to-end reconciliation and reporting solutions: matching logic, break dashboards, exception queues, settlement summaries, and standardized journals that feed downstream accounting, audit, and regulatory processes.
Own time-sensitive daily, weekly, and monthly reconciliations across card networks, banking partners, processors, and internal transaction and ledger data, including full ownership of discrepancy management from detection through root cause, corrective action, and control improvement.
Translate ambiguous business, finance, and regulatory needs into concrete measurement systems: define and roll out key metrics for the reconciliation and reporting domain (match rates, break aging, time-to-resolution, funding compliance, reporting SLAs) and ensure stakeholders interpret them in the correct context.
Serve as the subject matter expert on settlement, funding, and money-movement flows; field questions on transaction lifecycles, data models, and the reconciliation tech stack from stakeholders and leadership.
Own the design, development, and documentation of automated SQL-based reporting using best practices, navigating new and unfamiliar datasets to answer complex questions about the flow of funds.
Work independently or partner with data engineering to design, build, validate, troubleshoot, and maintain the datasets and pipelines that power reconciliation and reporting, making sound trade-offs between accuracy, implementation effort, and complexity.
Proactively identify control gaps, revenue leakage, manual toil, and upstream data-quality issues; drive the automation and process improvements that fix them, and monitor daily settlement and banking activity for irregularities.
Own relationships with technical and non-technical stakeholders across Engineering, Product, Accounting, Treasury, Tax, and Compliance; directly influence the priorities, decisions, and roadmap of the team and its partners.
Lead month-end close support for the domain: reconciliation reporting, standardized summaries, and audit-ready documentation, including supporting internal and external audits.
Define business requirements and test plans for system changes, validate new processes and reconciliation capabilities before deployment, and partner with Engineering and Data teams to resolve bugs and ship enhancements.
Help onboard and mentor other analysts, including reviewing code and evangelizing reconciliation and reporting best practices.
Apply an AI-first mindset to improve the speed, quality, and insight of analytical work, and guide responsible AI use on the team.