Position Title: Senior Data Engineer
Company Story:
Company Story:
- Inc. 5000 Fastest-Growing Company - 9 out of the past 12 years
- Inc. Hall of Fame recognition for sustained growth (fewer than 1% of companies achieve this)
- NEO Success Award - 4 consecutive years based on revenue, employment, and growth
- Ernst & Young Entrepreneur of the Year Award Winner
- Weatherhead 100 Fast Growth List
- Generous health and retirement options
- Progressive bonus structure aligned with company performance
- Hybrid schedule - 1 day per week on-site
- Culture of smart people solving complex problems in a fast-moving environment
- PTO is for personal time only - sick days are separate
- Annual team trip to Mexico for top performers
- Design and build scalable data pipelines using Python, PySpark, and Databricks - powering client-facing analytics and insights products
- Build and manage data orchestration workflows using Dagster and ML pipeline orchestration using Argo and Kedro
- Architect and optimize data models across Azure (ADF, Synapse, ADLS, Blob Storage, Event Hubs)
- Write production-grade, object-oriented Python code in a Python-first engineering culture
- Collaborate with data science teams to productionize models and analytical outputs
- Drive the platform's evolution - away from ADF-style orchestration toward pure Python pipelines, modern orchestration, and Agentic AI
- Actively use AI coding assistants (Claude Code, Copilot, or equivalent) to accelerate development and champion AI-assisted practices across the team
- Partner with engineering leadership on architecture decisions and mentor junior and mid-level engineers on best practices
- Senior-level Python development - clean, production-ready, object-oriented code
- Understanding of modern, code-first pipeline design - and a desire to move beyond legacy orchestration approaches like ADF
- Strong PySpark for large-scale data transformation
- Dagster, Argo, or Kedro experience or strong Python/Databricks engineers with genuine interest in modern orchestration
- Fluent SQL - windowed aggregates, complex joins, query optimization
- Azure data services breadth: Synapse, ADLS, Blob Storage, Event Hubs, Cosmos DB
- Experience supporting ML/AI model deployment or data science pipelines - MLFlow and Postgres are part of the current ecosystem
- Comfortable using AI coding assistants (Claude Code, Copilot, or equivalent) as part of daily development workflow
- Exposure to Agentic AI concepts or LLM-integrated pipeline design