Senior Staff Data Engineer

Afresh is an AI platform for grocery, focused on reducing food waste through innovative technology. As a Senior Staff Data Engineer, you will set technical direction and build core data systems that power Afresh's products, tackling complex data challenges and ensuring high-quality integrations.

Responsibilities:

• 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

Requirements:

• 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
• Experience in grocery, retail, or supply chain data domains
• Prior experience at a high-growth startup navigating rapid customer expansion
• A history of acting as a technical leader who sets direction across multiple teams or projects