Data Engineering built for Telecom companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Telecom companies, this means navigating FCC regulations (US), GDPR (EU) while shipping fast.
Who needs Data Engineering for Telecom?
- Network performance monitoring at massive scale
- Legacy billing systems resistant to modernization
- Customer churn driven by poor self-service tools
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Telecom platforms operate at a scale where even small inefficiencies translate into massive infrastructure costs.
We've designed our Data Engineering process specifically around the realities of Telecom businesses in .
Stop guessing on Data Engineering — let's build a real plan together
Book a free 30-minute discovery callThe Data Engineering challenges unique to Telecom in
- Network performance monitoring at massive scale
- Legacy billing systems resistant to modernization
- Customer churn driven by poor self-service tools
- 5G and IoT integration complexity
- Regulatory reporting across multiple jurisdictions
How GarudLabs approaches Data Engineering for Telecom companies 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:
- FCC regulations (US)
- GDPR (EU)
- Telecom data retention laws
- Net neutrality regulations
Proven Results
"We helped a telecom provider reduce customer churn by 18% with a self-service billing and support portal."
Read the full case studySee how GarudLabs can deliver Data Engineering for your team
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 telecom projects addressing challenges like network performance monitoring at massive scale. We helped a telecom provider reduce customer churn by 18% with a self-service billing and support portal.
For telecom clients, we pay close attention to FCC regulations (US), GDPR (EU), 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 telecom clients include network performance monitoring at massive scale and legacy billing systems resistant to modernization. We tailor our discovery process to surface the specific version of these problems your business faces.