Business Intelligence Specialist
Most applications go out cold — see where you stand first. No sign-up to start.
Don't just apply. Show up ready.
Olive works from this exact posting — no sign-up to start.
At a glance
Job overview
Stockbit is hiring a Business Intelligence Specialist. The BI Specialist will focus on finance and settlement analytics, collaborating with Finance, Operations, and Engineering teams to ensure accurate and timely reporting on transactions, settlements, and financial performance. This role involves building and maintaining dashboards, reconciliation reports, and data pipelines, while ensuring data integrity across settlement flows. The specialist will also investigate issues and document reporting logic.
Key focus areas include Ensure data accuracy, consistency, and governance across finance-related reporting, Collaborate cross-functionally to investigate issues and document reporting logic, and Manage multiple reporting requests concurrently, prioritizing based on business urgency and impact.
Successful candidates bring Business Intelligence Experience and Cross‑Functional Collaboration Ability. Important skills include SQL, Collaboration, Communication Skills, Data Accuracy, Data Consistency, and Data Governance. Preferred (not required): Settlement Concepts.
Skills & qualifications
Skills
Qualifications
Full job description
About The Role
We are seeking a BI Specialist to focus on finance and settlement analytics, partnering closely with Finance, Operations, and Engineering teams to ensure accurate, timely, and trusted reporting on transactions, settlements, and financial performance. You will build and maintain the dashboards, reconciliation reports, and data pipelines that finance and operations teams rely on daily, while ensuring data integrity across settlement flows.
Key Responsibilities
- Ensure data accuracy, consistency, and governance across finance-related reporting.
- Collaborate cross-functionally to investigate issues and document reporting logic.
- Manage multiple reporting requests concurrently, prioritizing based on business urgency and impact.
- Design, build, and maintain dashboards and reports related to settlement and financial performance.
- Partner with Finance and Operations to define and standardize settlement-related metrics (e.g., settlement time, failed/pending transactions, reconciliation discrepancies, payout accuracy).
- Monitor daily/weekly settlement data for anomalies, discrepancies, or delays, and escalate issues proactively.
- Build and maintain data pipelines that consolidate transaction and settlement data from multiple sources (payment gateways, banks, internal ledgers) into a single source of truth.
- Support month-end/quarter-end close processes by providing accurate settlement and reconciliation reports.
- Investigate root causes of settlement discrepancies in collaboration with Engineering and Finance teams.
- Document data definitions, reconciliation logic, and reporting processes for auditability and knowledge continuity.
Requirements
- 1–3 years of experience in Business Intelligence, Finance Analytics, or a related field (settlement/payments experience strongly preferred).
- Strong proficiency in SQL and modern BI tools (e.g., Tableau, Power BI, or similar).
- Understanding of settlement/reconciliation concepts (e.g., payment gateways, transaction lifecycles, chargebacks, payouts) is a strong plus.
- Working knowledge of Python and/or DBT is a plus.
- Ability to work cross-functionally with Finance, Operations, and Engineering teams.
- Good communication skills, with ability to explain data/reconciliation issues clearly to non-technical stakeholders.
- Experience with stock investing or financial data analysis is a plus.
Non-Negotiable
Candidates must have at least 1 year of hands-on experience in a Data Analyst or Business Intelligence role, with prior experience working with financial and settlement data (e.g., transactions, settlements, payments, investments, banking, brokerage, fintech, or other financial datasets). Candidates should be able to clearly explain how they utilized the data to generate insights and support business decisions.
You've read the whole posting — now see how you match it.