Data Engineering built for Water Management companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Water Management companies, this means navigating EPA water quality regulations (US), EU Water Framework Directive while shipping fast.
Who needs Data Engineering for Water Management?
- Aging infrastructure limiting real-time monitoring
- Leak detection and water loss tracking accuracy
- Regulatory reporting for water quality compliance
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Utility-grade water systems software has to be reliable enough that a bug never becomes a public health issue.
Water Management founders and CTOs in trust GarudLabs with Data Engineering because we communicate like an in-house team.
See how GarudLabs can deliver Data Engineering for your team
Book a free 30-minute discovery callCommon Data Engineering mistakes we see across Water Management teams in
- Aging infrastructure limiting real-time monitoring
- Leak detection and water loss tracking accuracy
- Regulatory reporting for water quality compliance
- Integrating SCADA systems with modern dashboards
- Customer usage and billing transparency expectations
How we de-risk Data Engineering for Water Management teams 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:
- EPA water quality regulations (US)
- EU Water Framework Directive
- Local utility compliance standards
- SCADA security regulations
Proven Results
"We helped a water utility cut non-revenue water loss by 17% with a leak detection monitoring platform."
Read the full case studyBring your Data Engineering idea to a team that ships for Water Management
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 water management projects addressing challenges like aging infrastructure limiting real-time monitoring. We helped a water utility cut non-revenue water loss by 17% with a leak detection monitoring platform.
For water management clients, we pay close attention to EPA water quality regulations (US), EU Water Framework Directive, 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 water management clients include aging infrastructure limiting real-time monitoring and leak detection and water loss tracking accuracy. We tailor our discovery process to surface the specific version of these problems your business faces.