Data Engineering built for Healthtech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Healthtech companies, this means navigating HIPAA, HITECH while shipping fast.
Who needs Data Engineering for Healthtech?
- Navigating HIPAA and data privacy requirements
- Integrating with fragmented EHR/EMR systems
- Designing for clinician workflows, not just patient apps
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Patient data, clinical workflows and care outcomes all depend on software that clinicians actually trust.
Scaling Healthtech operations in usually means investing in Data Engineering sooner than expected.
Schedule a free Data Engineering discovery call with our Healthtech team
Book a free 30-minute discovery callSigns your Healthtech company in needs better Data Engineering support
- Navigating HIPAA and data privacy requirements
- Integrating with fragmented EHR/EMR systems
- Designing for clinician workflows, not just patient apps
- Ensuring uptime for mission-critical care tools
- Managing interoperability across health data standards
Why Healthtech companies in trust us with Data Engineering
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:
- HIPAA
- HITECH
- FDA SaMD guidelines
- GDPR (EU)
- HL7/FHIR standards
Proven Results
"We helped a telehealth startup reduce no-show rates by 38% with an automated scheduling and reminder system."
Read the full case studyGet a clear Data Engineering roadmap for your Healthtech 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 healthtech projects addressing challenges like navigating hipaa and data privacy requirements. We helped a telehealth startup reduce no-show rates by 38% with an automated scheduling and reminder system.
For healthtech clients, we pay close attention to HIPAA, HITECH, 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 healthtech clients include navigating hipaa and data privacy requirements and integrating with fragmented ehr/emr systems. We tailor our discovery process to surface the specific version of these problems your business faces.