+ Post Job +
Home β€Ί Fintech & Crypto

Open Banking Integration Specialist

πŸ“ Anywhere 🏷️ Fintech & Crypto πŸ’° $90,000 / year

Banks that plug into open banking rails move real customer transaction data every few seconds, and someone has to make sure the numbers landing on the other end still add up. That is the core of this role: financial analysis applied specifically to open banking integrations, not general bookkeeping. The position is full-time and fully remote, with no office or city attached to it, open to candidates anywhere who can work through the analytical detail without losing accuracy under volume. Open banking is still a relatively young area of financial infrastructure, and companies building on it need people who can catch problems in the data before those problems reach a customer statement.

The role

Open banking integrations connect a customer's bank account directly to a third-party financial product, which means the data pipeline behind that connection needs constant oversight rather than a one-time setup check. When an integration goes live for a new banking partner, transaction volume through that pipeline can jump within days, and the reconciliation workload jumps with it.

You will analyze financial data and transaction flows tied to open banking connections, tracking how funds and account information move once a client's system links to a bank's API. Reconciliation is a constant part of the job, not an occasional task.

  • Analyze financial data and transactions related to open banking integrations
  • Prepare reports and reconciliations that account for every discrepancy, not just the obvious ones
  • Flag discrepancies or risk indicators as soon as they surface, before they compound
  • Support budgeting, forecasting, and compliance processes connected to open banking work
  • Document reconciliation methodology so the same discrepancy does not need re-investigating from scratch later

One recurring scenario: a reconciliation run flags a batch of transactions where the settlement timestamps do not match the bank feed exactly, often by seconds. Working out whether that is a timezone artifact or a genuine data gap is the kind of problem this role is built to solve, and it happens more weeks than not. Reports you produce feed directly into decisions other teams make about which integrations are stable enough to expand, so accuracy matters more than speed, though both are expected.

Requirements

You will need a bachelor's degree in finance, accounting, or economics as the baseline, along with two years of hands-on experience specifically in open banking integration work. Proficiency with financial software and genuinely strong analytical skills matter more here than years alone; a candidate with sharp instincts and eighteen months of directly relevant work has sometimes outperformed someone with a longer but less focused resume.

What tends to separate a strong candidate from an adequate one is comfort with ambiguity: raw transaction data rarely arrives clean, and the job requires deciding what a gap actually means before writing it up. A background in general accounting reconciliation transfers reasonably well, though it usually takes a few weeks to adjust to the pace and volume that an active open banking feed produces compared to a standard monthly close cycle.

Skills that matter

The must-have list is short but specific:

  • Financial modeling
  • Strong Excel skills, including pivot tables and lookup formulas
  • Comfort inside accounting or ERP software
  • Analytical thinking that holds up under a pile of transaction records

Nice-to-have skills include prior exposure to open banking APIs or PSD2-adjacent frameworks, experience with dedicated reconciliation software, or progress toward a CFA or similar analytical credential. None of the nice-to-haves are disqualifying on their own; they simply shorten the ramp-up period once you start.

Compensation and benefits

This role pays 90,000 dollars a year. This posting reached you through Remoteroles, where fintech-adjacent remote roles like this one tend to fill quickly once a candidate with the right analytical background applies. The full package extends past salary.

  • Health coverage for you and eligible dependents
  • Paid time off that accrues from your start date
  • Retirement plan matching up to a set percentage of salary
  • Annual performance bonuses tied to individual and team results

Bonus payouts are based on a mix of individual accuracy metrics, how clean your reconciliations run, and broader team goals around integration stability, so the incentive lines up with the actual work rather than sitting apart from it.

Remote work in practice

Standard collaboration tools carry most of the day: a shared reporting dashboard, a ticketing system for flagged discrepancies, and video calls scheduled around a core overlap window rather than a fixed nine-to-five for everyone on the team. New analysts usually pair with a more senior team member for the first few weeks to learn how a given client's data feeds are structured before working independently.

There is no physical office for this role and no country requirement beyond being able to work the hours the position needs. Most days involve independent analytical work, broken up by scheduled check-ins with the finance team to walk through reconciliation results or flag a risk that needs escalation. Expect a few hours of overlap with a core working window most weekdays, arranged through calendar tools and a shared reporting dashboard, so real-time questions do not sit for a full day waiting on a reply.

Async documentation carries a lot of weight on a distributed finance team. Reports and reconciliation notes need to be clear enough that a colleague in a different time zone can pick up where you left off without a live call to explain it.

Month-end close is the one stretch where the async rhythm tightens up. Expect more frequent check-ins during that window, since numbers need to be finalized on a hard deadline rather than a rolling one, and a delayed reconciliation at that point can hold up reporting for the whole finance function.

Next steps

Apply with a resume that spells out your specific open banking or financial-integration experience rather than general accounting duties, since that distinction is what reviewers look for first. Include any relevant software platforms you have used. Shortlisted candidates can expect an initial screening call followed by a technical conversation focused on a sample reconciliation scenario, and a final conversation with the finance lead this role reports to.

That technical conversation usually includes a walk-through of a sample dataset with a deliberate discrepancy planted in it, mostly to see how a candidate reasons through the problem out loud rather than to test whether they land on the exact right answer. Being able to explain your logic clearly matters as much as being correct.

Frequently Asked Questions

You're tracking how funds and account information move once a client's system links to a bank's API through an open banking connection, and reconciling discrepancies constantly rather than as an occasional task. One recurring example is settlement timestamps that don't match the bank feed by a matter of seconds, and working out whether that's a timezone artifact or a genuine data gap.
The listing asks for two years of hands-on experience specifically in open banking integration work, though it also notes a candidate with sharp instincts and eighteen months of directly relevant work has sometimes outperformed someone with a longer but less focused resume.
Async documentation carries a lot of weight normally, but month-end close is the one stretch where the rhythm tightens up. Expect more frequent check-ins during that window, since numbers need to be finalized on a hard deadline and a delayed reconciliation can hold up reporting for the whole finance function.
They're based on a mix of individual accuracy metrics, how clean your reconciliations run, and broader team goals around integration stability, so the listing says the incentive lines up with the actual work rather than sitting apart from it.
It usually includes a walk-through of a sample dataset with a deliberate discrepancy planted in it, mostly to see how you reason through the problem out loud rather than whether you land on the exact right answer.
Apply Now