Data engineering & warehouse consulting
Infrastructure your
finance team can
audit at 2am.
AZ Data designs, migrates, and hardens warehouse-grade data platforms — Snowflake architecture, dbt pipelines, Airflow orchestration, and schema governance — augmented with Claude-powered tooling for documentation, change tracking, and pipeline automation.
Services
Four problems we're usually called in for
Each engagement starts narrow — one warehouse, one pipeline, one migration — and is scoped to leave you with documentation and ownership, not a dependency on us.
01 · architecture
Warehouse design & migration
Dimensional models, Data Vault, or a pragmatic hybrid — built for the reporting your business actually runs, and migrated off legacy platforms without a reconciliation nightmare.
02 · pipelines
dbt & Airflow engineering
Transformation logic that's tested, versioned, and readable by the next engineer — orchestrated on schedules and dependencies that match how the business actually operates.
03 · security
Access & platform hardening
Role hierarchies, key-pair auth, MFA enforcement, and inactive-account cleanup — the unglamorous work that keeps an audit from becoming an incident.
04 · governance
Schema tracking & documentation
Automated diffing of DDL changes across environments, with a living record of what changed, when, and why — so "who touched this table" is a query, not an investigation.
AI & Claude integration
The warehouse, made queryable in plain language
We build with Claude and the Anthropic API directly on top of the platforms we operate — so documentation, schema history, and pipeline logic stay answerable, not just archived.
agent workflows
Claude-powered data assistants
Internal agents built on the Claude API that answer "what changed in this table and why" against real DDL history — not a static wiki page nobody updates.
mcp
MCP servers for your data stack
Model Context Protocol connectors that let Claude read schema, lineage, and pipeline state directly from Snowflake, dbt, and Airflow — grounded answers, not guesses.
automation
Claude Code in the pipeline
Agentic coding workflows for migration scripts, dbt model scaffolding, and Airflow DAG generation — reviewed by engineers, not shipped unsupervised.
governance
Change tracking, explained in language
Hash-diffed schema changes converted into structured, human-readable summaries — so audits and onboarding start from a narrative, not raw DDL.
Approach
How we work
no black boxes
Your team owns everything we build
Every model, DAG, and policy is documented and handed over — the goal of an engagement is to make future outside help optional, not recurring.
production first
We design for the incident, not the demo
Alerting, rollback paths, and access boundaries are part of the first draft — not a hardening pass added after something breaks.
narrow scope
Small, verifiable engagements
We'd rather ship one warehouse migration cleanly than run an open-ended retainer neither side can measure.
Stack
Tools we work in daily
Contact
Tell us what's breaking
Describe the pipeline, migration, or audit you're staring down. We'll reply with whether it's a fit before either of us spends real time on it.
- Email hello@azdata.app
- Based in Baku, Azerbaijan · Tallinn, Estonia
- Focus Fintech & regulated data platforms