Service
Data engineering
Luciérnaga Labs builds data pipelines, integrations and data platforms that turn information scattered across systems into reliable data a business can make decisions with. That goes well beyond a dashboard: ingestion, ETL and ELT, data modeling, quality checks and the infrastructure that keeps them running. The studio is based in Colombia and works with clients around the world, remotely.
What are the signs a company needs data engineering?
- Reports are rebuilt by hand from exports every week
- The same number differs depending on who you ask
- Important data is locked in systems that don’t integrate
- AI projects stall because the data isn’t ready
What do we build?
- Data pipelines
- ETL and ELT
- Integration of business systems
- Data architecture and modeling
- Data platforms
- Analytics engineering
- Business-intelligence infrastructure
Why does data engineering come before AI?
AI systems are only as reliable as the data they read. Most enterprise AI work starts with clean, documented and accessible data, which is why the two services are designed to work together.
Frequently asked questions
Do you build dashboards?
Yes, on top of a reliable data layer. A dashboard over inconsistent data only makes the inconsistency easier to see.
Which tools do you use?
Most often Python, PostgreSQL and AWS. We work with the databases and warehouses a company already runs when they fit the problem.
Do you work with companies outside Colombia?
Yes. We work remotely with teams worldwide, in English or Spanish. We work on US Eastern/Central hours (UTC−5), with good overlap with the US West Coast, Latin America and European mornings.