Data engineering for financial services
We build the data pipelines that financial services depend on for regulatory reporting, risk and customer data: governed ELT with provable quality, lineage and audit, delivered by one accountable Veratas team.
In financial services, the data has to be right and provably so
A financial services data estate is judged not only on what it produces but on whether every figure can be traced and trusted.
Financial services organisations run on data that feeds regulatory submissions, risk calculations, capital reporting and customer decisions. Regulators expect those submissions to be accurate, complete and delivered on time, and they expect the firm to be able to show how each number was produced. A reporting pipeline is therefore not just plumbing; it is part of the firm’s regulatory posture.
That raises the bar on data quality. Errors that might be tolerable elsewhere become material when they flow into a risk model or a regulatory return. Customer data carries its own weight, with privacy obligations and the need for a consistent, de-duplicated view across products and systems. Data engineering in this sector has to treat correctness as a first order requirement, not a later clean up.
Lineage and auditability are the other half of the picture. When an auditor or regulator asks where a figure came from, the firm needs a clear, documented answer covering source, transformation and control. Veratas builds pipelines where quality is checked, lineage is recorded and the whole flow stands up to scrutiny, delivered by one accountable team accredited to ISO 27001, ISO 9001 and CMMI Level 3.
What strong data engineering changes for financial services
The areas where well built pipelines turn raw data into reporting and risk inputs the firm can defend.
Pipelines for regulatory reporting
We build ELT pipelines in Azure Data Factory that assemble regulatory datasets on a dependable schedule, so submissions are complete, consistent and produced through a controlled, repeatable process.
Risk data, assembled correctly
We engineer the pipelines that feed risk and capital calculations, bringing positions, exposures and reference data together into clean, modelled datasets so risk teams work from a reliable base.
A consistent customer view
We integrate customer data across products and systems, resolving duplicates into a single consistent view, so reporting, risk and service decisions all draw on the same dependable record.
Data quality as a control
We embed validation, reconciliation and exception handling into every pipeline, so errors are caught and surfaced before data reaches a regulatory return or a risk model.
Lineage and audit evidence
We record end to end lineage with Microsoft Purview, so any reported figure can be traced through transformation back to source, giving auditors and regulators a clear, documented answer.
How Veratas delivers data engineering for financial services
A controlled route from fragmented data to governed, auditable reporting and risk pipelines.
Map data and obligations
We catalogue source systems, reporting and risk requirements and data ownership, and design the lakehouse and pipeline architecture around what the firm must produce and prove.
Build governed ELT pipelines
We implement ELT pipelines in Azure Data Factory into a lakehouse on Microsoft Fabric, with transformations defined as controlled, version managed code.
Embed quality and lineage
We add validation, reconciliation and exception handling, and capture end to end lineage in Microsoft Purview, so correctness and traceability are built in, not bolted on.
Operate and evidence
We run the pipelines as a managed service with monitoring and alerting, and maintain the evidence that keeps reporting audit ready.
FAQ
Frequently asked questions
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Related industry solutions
Other ways Veratas applies Microsoft and data engineering to industry-specific challenges.
Data engineering for energy and utilities
We build the data pipelines that turn sensor, grid and asset data into a trustworthy foundation for energy and utilities: real-time and batch ingestion, a governed lakehouse and forecasting inputs, delivered by one accountable Veratas team.
Microsoft Fabric for financial services
Microsoft Fabric brings risk, customer and transaction data into one governed lakehouse so financial services firms can report, manage risk and serve customers with confidence.
Power BI for financial services
Power BI gives financial services firms governed regulatory, risk and performance reporting they can stand behind.
Build reporting and risk pipelines you can defend
Book a discovery call and we will review your reporting, risk and customer data, then set out a clear route to governed, auditable pipelines.