Data Engineering built for Banking companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Banking companies, this means navigating Basel III, PSD2 (EU) while shipping fast.
Who needs Data Engineering for Banking?
- Core banking systems resistant to modernization
- Real-time payment processing requirements
- Open banking API integration complexity
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Core banking software has to modernize without ever putting customer deposits or trust at risk.
Most Data Engineering projects fail on communication, not code — we fix that for Banking clients in .
Get a Data Engineering proposal tailored to your Banking goals
Book a free 30-minute discovery callSigns your Banking company in needs better Data Engineering support
- Core banking systems resistant to modernization
- Real-time payment processing requirements
- Open banking API integration complexity
- Fraud detection across digital channels
- Regulatory reporting across jurisdictions
Our process for delivering Data Engineering to Banking clients
Data warehouse architecture (Snowflake, BigQuery)
ETL/ELT pipeline development
Data quality monitoring and alerting
BI dashboard integration
Data governance and access controls
Core Technology Stack
SnowflakeBigQueryAirflowdbtPythonKafkaAWS Glue
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $140,000
Data Engineering engagements in this combination typically need to account for:
- Basel III
- PSD2 (EU)
- Dodd-Frank (US)
- AML/KYC regulations
Proven Results
"We helped a digital bank reduce account opening time from days to under 10 minutes with a custom onboarding flow."
Read the full case studyReady to talk Data Engineering for your Banking business in ?
Get a free project cost estimateFrequently Asked Questions
Most Data Engineering engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Data Engineering projects with us typically range from $25,000 - $140,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For data engineering, we typically work with Snowflake, BigQuery, Airflow, dbt, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical data engineering engagement includes data warehouse architecture (snowflake, bigquery), along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for data engineering because of data scattered across disconnected systems, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple banking projects addressing challenges like core banking systems resistant to modernization. We helped a digital bank reduce account opening time from days to under 10 minutes with a custom onboarding flow.
For banking clients, we pay close attention to Basel III, PSD2 (EU), building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for banking clients include core banking systems resistant to modernization and real-time payment processing requirements. We tailor our discovery process to surface the specific version of these problems your business faces.