Data Engineering Beratung
Data Engineering & ETL that holds up in production
We build data platforms that carry daily decisions, ML features, and operational workflows — versioned, tested, and documented from day one.
From source chaos to usable data products
CRM, ERP, product data, event streams, and manual exports become versioned, tested, documented data models.
- Source mapping and data-quality audit
- ELT/ETL with dbt, Airflow, or Dagster
- Semantic layers for analytics and ML
Governance without bureaucracy
We set up lineage, tests, role models, and cost control so teams move faster and compliance questions stay answerable.
- PII classification and access concepts
- Snowflake, BigQuery, Redshift, or Databricks
- Monitoring, alerting, and runbooks
FAQ
Which data stack do you work with?
Primarily dbt, Airflow/Dagster, and a cloud warehouse (Snowflake, BigQuery, Redshift, or Databricks). We choose maintainable components your team can own long-term.
Can you fix our existing pipelines?
Yes. We frequently come in to stabilize fragile ELT, add tests and lineage, and reduce warehouse cost rather than rebuild from scratch.
Let's talk about your data platform
Book a short audit call — we'll assess your current setup and the highest-impact next step.
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