We are hiring a Lead, Data & Tools Engineering to own our data infrastructure, build and maintain internal tools, and bring a product-engineering mindset to Tutor Success. This is not a traditional data analyst role — AI handles our analysis. We need someone who can pull data from our systems, build tools the team uses daily, and think like a product engineer while shipping fast with AI.
What You Will Own
- Build and maintain internal dashboards, operational tools, and automation systems used daily by the Tutor Success team
- Extract, transform, and model data from Redshift, Periscope, Google Sheets, and internal API's
- Own the full lifecycle of internal tools — from requirements gathering to deployment to iteration
- Build rapidly using AI tools (Claude Code, LLM APIs) — prototype, ship, and iterate
- Maintain and improve existing dashboards (Flask, Python, Chart.js) deployed on AWS EC2
- Collaborate with central engineering and product teams to integrate tutor success data into company-wide systems
- Think like a product manager for internal tools — prioritize based on team impact, scope features, ship MVPs
Who You Are
- 4-8 years in data engineering, full-stack development, or internal tools / product engineering
- Strong in Python and SQL — can write clean Redshift queries, build Flask apps, and script automations
- Comfortable with cloud infrastructure — AWS EC2, basic DevOps, deployments, service management
- AI-native mindset — actively uses AI coding tools (Claude Code, Copilot, or similar) and is excited about building with LLMs
- Product thinking — understands user needs, scopes features, and ships solutions that solve real problems
- Self-starter who thrives with ownership — you will be the technical backbone of a non-engineering team
- Clear communicator — can explain technical trade-offs to non-technical stakeholders
Preferred Background
- Internal tools, growth engineering, or ops-tech roles at startups or ed-tech companies
- Experience building dashboards or data products for operations teams
- Familiarity with data warehouses (Redshift, BigQuery) and BI tools (Periscope, Metabase, Looker)
- Exposure to AI/LLM-based development workflows
