Data Engineering built for SportsTech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For SportsTech companies, this means navigating GDPR, Anti-doping data regulations while shipping fast.
Who needs Data Engineering for SportsTech?
- Real-time stats and fan engagement during live events
- Athlete performance data fragmentation
- Ticketing and access management complexity
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Fan engagement and athlete performance platforms compete for attention in real time, during the event itself.
We've designed our Data Engineering process specifically around the realities of SportsTech businesses in .
Bring your Data Engineering idea to a team that ships for SportsTech
Book a free 30-minute discovery callWhat SportsTech leaders in wish they knew before starting Data Engineering
- Real-time stats and fan engagement during live events
- Athlete performance data fragmentation
- Ticketing and access management complexity
- Sponsorship and media rights integration
- Mobile-first experience expectations from fans
How we tailor Data Engineering to SportsTech-specific requirements
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:
- GDPR
- Anti-doping data regulations
- Ticketing consumer protection laws
- Broadcast rights compliance
Proven Results
"We helped a sports league increase live app engagement by 45% during match days with real-time stats features."
Read the full case studyBring your Data Engineering idea to a team that ships for SportsTech
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 sportstech projects addressing challenges like real-time stats and fan engagement during live events. We helped a sports league increase live app engagement by 45% during match days with real-time stats features.
For sportstech clients, we pay close attention to GDPR, Anti-doping data regulations, 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 sportstech clients include real-time stats and fan engagement during live events and athlete performance data fragmentation. We tailor our discovery process to surface the specific version of these problems your business faces.