Afresh - Senior Staff Data Engineer

• Architect and build core data systems and pipelines that power Afresh products, owning reliability and quality from raw data through to production. • Take on our most ambiguous, high-leverage data problems and drive them to a shipped solution — without waiting for a detailed spec. • Set technical direction: define the architecture, patterns, and abstractions that make customer integrations and product dataflows faster, cleaner, and more repeatable over time. • Drive data quality and pipeline reliability — invest in better alerting, self-healing patterns, and resilience to messy or incomplete real-world customer data. • Champion AI-forward engineering: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive work, and push the team to the bleeding edge of modern data engineering. • Raise the bar technically — review code and architecture decisions, pair with engineers on hard problems, and mentor across the team. • Collaborate deeply with Product, ML, Solutions Engineering, and customer-facing teams to scope work, unblock dependencies, and make sure what we build meets real customer needs. • What Makes You a Great Fit • We encourage all highly-qualified candidates to apply, even if they don't meet every listed qualification. • Extensive experience (typically 8+ years) building data engineering systems, with a track record of operating at a staff or principal level. • Deep technical expertise across Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar). • A history of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable. • Proven ability to own ambiguous, end-to-end problems and set technical direction in a fast-moving environment with no established playbook. • Genuine enthusiasm for AI-augmented engineering. You've experimented with AI coding tools, agentic workflows, or similar, and have a vision for how they can transform data engineering. • Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering. • Strong collaboration and influence skills — you're effective working across engineering, product, and customer-facing teams, and you can move others without formal authority.