Core Data Pipeline Development Services
Everything between your source systems and a warehouse your analysts trust, built so it keeps running after we hand it over.
Data ingestion frameworks
The layer that pulls data in from APIs, databases, files, and streams. We build it as a framework, not a pile of one-off scripts, so adding the next source is a config change, not a rebuild.
- Reusable connectors, not one-off scripts
- Handles schema drift without silent failures
- Incremental loads, not full reloads every night
ETL / ELT development
The transformation logic that turns raw data into something your business can use. We build on dbt, Airflow, and Spark, and we push transformation into the warehouse where it belongs. Batch and streaming both.
- dbt-first, tested transformations
- ELT into the warehouse, not brittle external ETL
- Documented models your team can extend
Workflow orchestration
The scheduler that runs it all in the right order and tells you the moment something breaks. We build on Airflow or Dagster, with retries, backfills, and alerting that actually reaches a human.
- Dependency-aware scheduling, no cron spaghetti
- Automatic retries and clean backfills
- Alerting that reaches a person, not a dead inbox
Pipeline testing and observability
The part everyone skips until a bad number reaches the CEO's dashboard. We build data quality tests, freshness checks, and lineage in from the start, so you catch a broken pipeline before your stakeholders do.
- Data quality tests on every critical model
- Freshness and volume checks, not just "did it run"
- Lineage so you can trace a bad number to its source
