Data Engineering Lead @ Branching Minds and Founder of Datoga.io.
I design and lead modern data platforms with Databricks, Spark, dbt, Dagster, Airbyte—turning messy data into reliable, governed, and cost-efficient pipelines.
- Leading a Data Engineering team building a new data architecture (files from multiple US school districts → reliable datasets powering apps and analytics).
- Running Datoga.io, a consultancy focused on Modern Data Stack, Data Quality/Governance, and AI-assisted automation.
- Modern Data Platforms: lakehouse design, ingestion → bronze/silver/gold, SCD/Snapshots, cost/perf tuning.
- Data Quality & Governance: contracts, tests, lineage, SLAs, access with Unity Catalog.
- Orchestration & Ops: Dagster jobs, event-driven pipelines, CI/CD for data, observability and alerts.
- Enablement: standards, templates, and docs that help teams ship faster with fewer regressions.
- Standardized ingestion across vendors and districts, reducing ad-hoc work and incidents.
- Introduced snapshot/SCD patterns to cut unnecessary reprocessing and improve downstream reliability.
- Evolved data quality checks and metadata to support governance and safer product releases.
- Drove a practical migration path toward a scalable lakehouse with clear ownership.
Databricks • Spark • dbt • Dagster • Airbyte • SQL • Python • Delta Lake • AWS (S3, Glue, Lambda, Athena)
Also used: Metabase, GitHub Actions, Terraform, APIs, Crawlers, GCP (BigQuery/PubSub) when needed.
I’m not actively job-seeking, but I’m open to selective conversations or short-term advisory/consulting that align with building resilient data platforms at scale.