Data Pipelines & ETL
Batch and streaming pipelines that collect, clean and load data from your apps, databases and APIs, and tell you when something breaks.
- Batch & streaming
- Data quality checks
- Documented
Boring pipelines are good pipelines.
Idempotent runs
Re-running a pipeline never duplicates data.
Version-controlled logic
Every transformation is code, reviewed and tested like software.
Documented lineage
You can trace every number back to its source.
Pipelines you can rely on.
Source connectors
APIs, databases, spreadsheets and files, extracted on schedule or on events.
Data quality checks
Schema, null and freshness checks that stop bad data at the door.
Transformations
Cleaning, deduplication and joins in version-controlled SQL or Python.
Monitoring & alerts
Failures and delays reported to the right people immediately.
What we build it with.
- Languages
- Python
- SQL
- Processing
- Apache Spark
- Kafka
- dbt
- Orchestration
- Airflow
- cron
- Destinations
- PostgreSQL
- MongoDB
Questions, answered.
Batch or real-time?
Most reporting is fine with hourly or daily batches. We add streaming with Kafka only where a decision genuinely needs live data.
Can you fix our existing pipelines?
Yes. We audit what exists, stabilise the fragile parts and document everything.
Who owns the pipelines?
You do. Code lives in your repository and runs in your infrastructure.
Other Data Engineering services.
Data Warehousing
One well-modelled source of truth for reporting and analysis.
BI Dashboards & Reporting
Dashboards that answer the questions your team asks every week, refreshed automatically.
Have a project in mind?
Tell us what you're building, what's slowing your team down or what you'd like to automate. We'll come back with honest next steps and a clear estimate.
No obligation and no sales script.