Analytics engineering + applied AI
I'm Josh Bickmeyer. I've spent more than 12 years building data products that help teams answer real business questions. Lately, I've been applying the same discipline to AI workflows.
I work where data engineering meets
business decisions.
Selected work
These projects show how I work. I start with the workflow. Then I make the boundaries obvious and keep the evidence needed to debug what happened.
Mission Control
Mission Control coordinates the work between an idea and a live release. It keeps research, PRDs, implementation, review, and deployment in one system.
I built approval gates into the places where an agent should stop and ask. Releases reuse the same artifact, so testing and production do not quietly drift apart.
AI Analytics Engineering
This personal platform ingests data with dlt, transforms it in dbt, runs through Airflow, and publishes BI-ready models for Power BI.
I use it to test whether AI can speed up repetitive analytics work without weakening model tests, lineage, or code review.
Personal AI Assistant
This system uses specialized agents and Postgres-backed memory to handle email triage, calendar digests, and outbound calls.
It is where I test the unglamorous parts of agent work. I limit permissions, require a human check, and make failures recoverable. If it is not worth maintaining, I cut it.
These are working personal projects, but their active repositories are private. My public repos and open-source contributions are on GitHub ↗.
What I bring
I've spent more than a decade taking messy business questions back to the data. That work has included dbt models, Python pipelines, and dashboards used by business teams.
These days I spend a lot of time on AI. I care less about demos than whether the workflow can be trusted in production. I like staying close to the code. When a pipeline fails at 6 a.m., someone should know what changed and where to look.
SQL, Python, dbt, Airflow, Snowflake, Redshift, AWS S3
GitHub Actions, CI/CD, Docker, testing, monitoring
Power BI, Tableau, semantic models, KPI design, forecasting
Agent workflows, RAG, AI-assisted engineering, human review
Experience
Insurance, consulting, consumer goods, and retail analytics.
AAA Life Insurance
Independent
Kellogg Company
Schwan's Consumer Brands
Start a conversation
If you're working through a brittle data platform or trying to put an AI workflow into production, I'd like to hear about it.