Do we need a data warehouse?

If you have data in 3+ systems and want to ask questions across them — yes. If you're a single-database product, not yet.

Snowflake vs BigQuery?

BigQuery if you're already on Google Cloud or analytics-heavy. Snowflake if multi-cloud. Both work; we use whichever fits your existing stack.

How long until I see dashboards?

Foundational dashboards live in week 3. Custom analytics models stack on top from week 4.

Service

Data & Pipelines

We build the ETL, warehousing, and analytics infrastructure that turns raw data into decisions.

Let's talk All services

What's included

ETL & ELT pipelines

Move data reliably between sources — APIs, databases, files, queues.

Data warehousing

Snowflake, BigQuery, Redshift — modelled with dbt for sanity.

Real-time streaming

Kafka, Kinesis, Pub/Sub for event-driven systems.

Analytics engineering

Metric layers, dashboards, business-readable models.

Data quality & lineage

Tests, monitoring, lineage tracking so you trust your numbers.

Migration & cleanup

Move off the legacy warehouse. Or just clean up the mess that's there.

When to choose this

Good fit if

Your team copies data between systems by hand
You have data in five places and reconciliation is a nightmare
Your dashboards lie to you and nobody knows why
You need real-time data and your batch jobs run nightly

Maybe not if

You have under 10 GB total and a spreadsheet works
You don't yet have data — start with the product first

Typical process

Map sources, sinks, current pain points.

Tech we use

AirflowdbtSnowflakeBigQueryPostgresKafkaAirbyteFivetranMeltano

Pairs well with

AI & Agentic Solutions

We build AI agents, RAG systems, voice and multi-modal interfaces that solve real problems.

DevOps & Infrastructure

We own your infrastructure end-to-end — cloud, network, deploys, on-call. So your team can build product.

Common questions about data & pipelines

Let's scope this together.

Book a call Send a brief