HIRE REGTECH DEVELOPERS

Hire RegTech Developers: The Engineers Who Turn Regulatory Obligations Into Automated Infrastructure

RegTech developers build automated compliance infrastructure for regulated financial institutions. This includes things like regulatory reporting pipelines (COREP, FINREP, XBRL submissions), DORA compliance systems (ICT risk registers, incident reporting, resilience testing infrastructure), GRC automation platforms, and enterprise financial crime technology.

In order to do this, RegTech developers need a mixture of data engineering depth with regulatory domain knowledge, a combination that general engineers consistently lack.

Let’s look at the four sub-domains they work across, what separates qualified candidates from those who understand the frameworks without having built them, and how to staff this role.

If you are ready to hire RegTech developers who are handpicked based on your project requirements, request talent.

What RegTech Development Actually Requires

RegTech development closes that gap by building four categories of engineering infrastructure.

Reporting pipelines extract source data, validate it against regulatory data models (the EBA’s Data Point Model for COREP/FINREP, XBRL taxonomies, FinCEN’s BSA E-Filing schemas), transform it into required formats, and submit it through regulator-specified channels with full traceability back to source.

Compliance monitoring systems continuously check operational reality against regulatory requirements.

Risk data aggregation infrastructure consolidates data from multiple source systems into a unified model that satisfies BCBS 239’s requirements for accuracy, completeness, timeliness, and adaptability.

Operational resilience evidence systems produce the documentation DORA requires, because the regulation examines not just whether things happen but whether firms can prove they happened.

Hiring a general data engineer is not the right move here. 

Data engineers build pipelines that produce accurate outputs. RegTech engineers build pipelines that produce accurate outputs and can demonstrate to a regulator how those outputs were produced, what controls exist to detect when they aren’t, and who has access to the data at any point in the process.

It is critical to have a specialist on hand to avoid fines and a loss of user trust.

The Data Lineage Imperative: Why Most Organizations Fail BCBS 239

BCBS 239 has been in effect since 2016, but we’re still seeing cases where the ECB’s supervisory reviews find serious weaknesses in RDARR frameworks across significant institutions.

Most institutions fail BCBS 239 because they can’t demonstrate data lineage. In other words, they don’t have a complete, traceable chain from the number appearing in a regulatory report back to the source system record that produced it, through every transformation step in between.

A capital ratio or liquidity coverage ratio derives from dozens of source data attributes across multiple systems, including the general ledger, the risk engine, the position management system, and the collateral system.

Each attribute passes through extraction, transformation, validation, and aggregation before reaching the report. BCBS 239 requires every step to be documented, automated, and auditable.

Engineers who have built these pipelines against actual regulatory templates understand why this takes longer than a standard data engineering project and why the testing regime needs to be different.

DORA as Five Engineering Systems

DORA is described as a compliance framework. For engineering teams, it maps to five specific systems that must function and produce evidence.

1. ICT risk management: requires an asset and dependency register. This is a live inventory of all ICT systems, their classifications, their dependencies on internal systems and third-party providers, and their associated risk scores.

2. ICT incident reporting: needs automated classification and structured submission workflows. DORA mandates an initial notification within 4 hours of determining that an incident qualifies as “major.”

3. Digital operational resilience testing: requires an evidence platform tracking vulnerability assessments, penetration tests, and scenario-based resilience exercises, with remediation gap tracking and documentation.

4. ICT third-party risk management: needs a vendor risk monitoring platform covering the full contractual and operational assessment lifecycle, with concentration risk analysis and automated triggers when DORA-required contractual provisions appear absent or non-compliant.

5. Information sharing requires a threat intelligence intake pipeline consuming feeds from financial sector ISACs and mapping indicators to internal ICT assets.

The common requirement across all five is that every action, assessment, and vendor interaction needs to produce a timestamped, auditable record.

Related Reading: How to Choose the Right Software Development Partner

What RegTech Developers Cost

The combination of data engineering depth and regulatory domain knowledge places RegTech engineers at the upper end of the fintech engineering compensation range. 

According to Glassdoor, you can look at all-in costs of $154,000–$241,000 in the US market.

Demand comes from banks, large fintechs, insurance companies, and asset managers simultaneously, all competing for a pool that primarily comes from a narrow set of sources, which pushes prices up even further.

Here is what we are seeing in the market at the moment:

The average US time-to-hire for a senior RegTech engineer is also around 5–8 months, the longest search timeline in the compliance engineering cluster.

On the other hand, if you hire Trio’s LATAM nearshore model, pre-vetted RegTech engineers, you get people guaranteed to have the right skills, placed at $40–$90/hr.

Once they already have the right skillset, they just need to familiarize themselves with your specific requirements, which means they can be onboard in 3-5 days.

Related Reading: FinTech Recruitment Reshape: Strategies to Win Talent

Final Thoughts

RegTech is essential in the modern FinTech environment. Hiring a generic data engineer opens you up to several risks that could end up costing you a lot more than hiring the right people from the start.

These costs are not only made up of regulatory fines, but also a long-term loss of user trust.

If you are ready to hire RegTech developers today, book a discovery call.