Data Engineering built for EdTech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For EdTech companies, this means navigating FERPA, COPPA while shipping fast.
Who needs Data Engineering for EdTech?
- Low course completion and engagement rates
- Integrating video, assessments and certifications seamlessly
- Scaling infrastructure during enrollment spikes
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Learning platforms succeed or fail based on whether students actually finish what they start.
We've designed our Data Engineering process specifically around the realities of EdTech businesses in .
Let's scope your Data Engineering project — book a free call today
Book a free 30-minute discovery callCommon Data Engineering mistakes we see across EdTech teams in
- Low course completion and engagement rates
- Integrating video, assessments and certifications seamlessly
- Scaling infrastructure during enrollment spikes
- Meeting accessibility standards across devices
- Proving learning outcomes to institutional buyers
What makes our Data Engineering different for EdTech businesses in
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:
- FERPA
- COPPA
- GDPR (EU)
- WCAG accessibility standards
Proven Results
"We helped an online learning platform lift course completion rates by 27% with redesigned progress tracking."
Read how we built it for Ambition CollegeLet's scope your Data Engineering project — book a free call today
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 edtech projects addressing challenges like low course completion and engagement rates. We helped an online learning platform lift course completion rates by 27% with redesigned progress tracking.
For edtech clients, we pay close attention to FERPA, COPPA, 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 edtech clients include low course completion and engagement rates and integrating video, assessments and certifications seamlessly. We tailor our discovery process to surface the specific version of these problems your business faces.