Engineering & Infrastructure
Data Infrastructure & Analytics Foundations
3–8 weeksSources → warehouseDemo
Gathers and cleans your scattered data into one reliable place — ready for reporting and AI.
Integrated sources
8
in one place
Data freshness
15 min
always current
Quality checks
142
automated
If your analysts spend more time collecting and cleaning data than generating insights, the problem isn't their talent — it's the infrastructure.
We build data foundations that make your team significantly more productive: automated ingestion flows, reliable and clean data layers, and AI-ready pipelines. Technically: ETL/ELT with modern tooling (dbt, Airflow, Prefect), warehouse/lakehouse design, data catalog and lineage documentation, automated quality tests (Great Expectations or dbt tests), and streaming pipelines with Kafka or equivalent as needed.
Use cases
- —You need to integrate scattered data into a reliable warehouse or lakehouse
- —You are migrating platforms and want to preserve traceability and quality
- —You want to automate the data foundation that feeds reports and metrics
- —You need real-time, streaming, or recurring data pipelines
- —You want solid foundations for advanced analytics, ML, or feature stores
Deliverables
- —Production pipelines with orchestration (dbt, Airflow, or Prefect)
- —Warehouse/lakehouse design with documented data model
- —Data catalog and lineage documentation
- —Automated data quality tests (Great Expectations or dbt tests)
- —Data freshness SLA and common failure runbook
- —Pipeline monitoring dashboards