Profile
Frank Stevens
Building calm, durable data and web products.
Skills
Core tools and patterns I use across data, analytics, and product builds.
Data Engineering & Orchestration
Design and build warehouse layers and pipelines that are modeled, tested, and ready for reporting.
PostgreSQLdbtPythonApache Parquet- Relational modeling and SQL delivery (schemas, constraints, migrations)
- Warehouse transformations: staging to marts, incremental models, tests and documentation
- Pipeline design and orchestration (ETL/ELT, batch workflows, reliable execution)
Cloud & Data Platforms
Work across modern cloud environments and data platforms to support scalable analytics systems.
AzureAWSGoogle CloudGoogle BigQueryDatabricks- Cloud platforms (Azure, AWS, GCP)
- Data platforms (BigQuery, Databricks)
- Platform setup aligned with warehouse modeling and pipeline design
Analytics & BI
Deliver reporting and dashboards that remain consistent through shared definitions and clear models.
Power BIMetabasepandasNumPy- Semantic layer design and metric definition aligned with the data model
- Dashboarding and self-serve reporting with clear filters and drill paths
- Analysis and validation in Python to support reporting and decision-making
DevOps & Delivery
Ship and operate data systems with versioning, validation, and controlled delivery.
GitHub ActionsDockerTerraformRedis- CI/CD for data workflows (versioned pipelines, automated testing)
- Testing and data validation (dbt tests, schema checks)
- Security and access control (IAM roles, RLS policies)
Web Development
Build internal data tools and APIs that support ingestion, validation, and operational workflows.
TypeScriptNext.jsReactTailwind CSSNode.jsFastAPISupabase- TypeScript (Next.js, Node.js) for internal tooling and product surfaces
- API development (structured endpoints, validation, auth, versioning)
- Monorepo architectures (shared UI and domain logic)
Now playing
Straight from my headphones.
Checking Spotify...