Data infrastructure built for production reliability.
We build the pipelines, warehouses, and analytics infrastructure your business runs on — ingestion, transformation, streaming, and BI — with the testing and observability that make the numbers trustworthy.
From rebuilding fragile cron-driven ETL into tested dbt and Airflow, to designing a cost-controlled warehouse, to standing up real-time streaming, we treat data systems with the same production rigor as application code.
From ingestion to a trusted metrics layer.
Ingestion & ELT pipelines
Reliable extract-load pipelines from your sources into a warehouse, scheduled and monitored.
Warehouse & lakehouse design
Dimensional and lakehouse models built for query performance and cost control.
dbt transformation & testing
Versioned, tested transformations with lineage so analysts trust the numbers.
Streaming pipelines
Low-latency ingestion and processing for real-time analytics and event data.
Data quality & observability
Freshness, volume, and schema checks with alerting before bad data spreads.
BI & analytics enablement
Semantic layers and governed metrics so every dashboard agrees.
Model, build, validate, and operationalize.
Model & architect
We design the warehouse, models, and data contracts up front.
Build pipelines
We implement ingestion and transformation with tests.
Test & validate
We add quality checks and reconcile against source systems.
Operationalize
We schedule, monitor, and document so it runs itself.
Recent work, lightly anonymized.
Batch ETL to dbt + Airflow
Rebuilt fragile cron-driven ETL into tested dbt models orchestrated by Airflow, with full lineage.
Cost-controlled Snowflake
Designed a Snowflake warehouse with role-based access and per-team cost controls.
Streaming ingestion
Stood up Kafka-based streaming ingestion feeding real-time analytics dashboards.