Senior Data Engineer

Requirements

• Production data platform experience, on platforms such as Databricks, Snowflake, Spark, or dbt.
• 8+ years building software, weighted toward backend and data engineering.
• Expert SQL and deep experience with relational databases such as SQL Server, PostgreSQL, Oracle, or MySQL. We run SQL Server. You can read an execution plan, design indexes that hold up under load, and tell when a normalized model is the wrong choice.
• Experience writing back into a system of record. Transactional integrity, idempotency, and reconciliation.
• API design. You've designed APIs for applications you don't control, changed them without breaking those applications, and shaped them around what a UI needs.
• End-to-end delivery. You can point to features you drove from idea through POC, build, iteration, and release. We'll ask what you cut from scope, what you shipped rough, and what you killed.
• Caching and performance engineering. You've made slow things fast and can explain what you changed.
• Git, code review, and CI/CD. You work in Git, review other people's code, and ship through automated tests in a CI/CD pipeline.
• Data governance and security. Access controls, handling sensitive data, and meeting audit requirements.
• Production LLM systems you built and shipped, including what comes after shipping, such as evaluation, guardrails, cost, and latency.
• Day-to-day work with AI agents on production systems, with specifics on where they help and where they quietly fail.
• Building systems other people can audit. Lineage that holds up, parameters stored as versioned data, and outputs a non-engineer can challenge.
• Clear written communication. We write a lot of documents, and this role writes many of them.
• Strongly preferred
• 3+ years hands-on experience with a production data platform, including object modeling, building and shipping pipelines, and shipping an application that people use
• Python and PySpark, including catching what an agent gets wrong, such as a transform that looks right but skews the join, a window function that silently drops rows, or a fix that passes tests and breaks the contract downstream
• Dimensional modeling and schema design judgment
• Entity resolution, master data, taxonomies, or knowledge graphs
• React
• Process mining
• Jira, including connecting to it with Claude or other AI tools
• ERP integration experience • Streaming and event-driven ingestion (Kafka, CDC)
• Electronics distribution, supply chain, or industrial B2B data
• Explicitly not required
• A PhD
• Deep learning research or model training. We use frontier models; we don't train them
• Prior distribution-industry experience
• Front-end as a primary skill. The job is data and backend
• Ramp
• 30 days: You're shipping transforms and object-model changes to production through our existing promotion path, and you've found at least one thing we got wrong.
• 90 days: You're working across the backend, including the RMS write-back path, and an application you built is in daily use on the trading floor.
• Application Question Instead of a cover letter, we'd rather have your answer to one question: Describe something you built on a data platform that you'd model differently if you started again today, and what changed your mind. Our interviews include a hands-on build session. You'll use Claude, and you'll explain every line you ship.
• ERP integration experience
• Streaming and event-driven ingestion (Kafka, CDC)