Data Engineering built for GovTech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For GovTech companies, this means navigating WCAG accessibility standards, FedRAMP (US) while shipping fast.
Who needs Data Engineering for GovTech?
- Legacy government systems resistant to modernization
- Strict accessibility and compliance requirements
- Long procurement cycles slowing delivery
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Government software must serve every citizen, including those least comfortable with technology.
Data Engineering shouldn't feel like a gamble — GovTech teams in work with us because predictability matters.
Schedule a free Data Engineering discovery call with our GovTech team
Book a free 30-minute discovery callThe real cost of getting Data Engineering wrong in GovTech
- Legacy government systems resistant to modernization
- Strict accessibility and compliance requirements
- Long procurement cycles slowing delivery
- Public trust concerns around data handling
- Serving citizens across varying digital literacy levels
The GarudLabs framework for GovTech Data Engineering projects
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:
- WCAG accessibility standards
- FedRAMP (US)
- GDPR (EU)
- Public records and FOIA regulations
Proven Results
"We helped a municipal government cut permit processing time by 50% with a digital application portal."
Read the full case studyGet a Data Engineering proposal tailored to your GovTech goals
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 govtech projects addressing challenges like legacy government systems resistant to modernization. We helped a municipal government cut permit processing time by 50% with a digital application portal.
For govtech clients, we pay close attention to WCAG accessibility standards, FedRAMP (US), 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 govtech clients include legacy government systems resistant to modernization and strict accessibility and compliance requirements. We tailor our discovery process to surface the specific version of these problems your business faces.