SQL & Analytics Engineer Expert

Analytics engineers who live in dbt, BigQuery, and Snowflake to build the SQL scenarios frontier AI labs use to test model judgment. AfterQuery builds the expert evaluation data that frontier AI labs use to measure and improve their models. We're hiring analytics engineers as contractors to author and grade the SQL and data modeling scenarios those evaluations run on. What you'll actually do Author realistic analytics scenarios, from raw tables through tested data models Write reference answers with the modeling and query reasoning behind each decision Grade model output for SQL correctness and warehouse efficiency Flag queries that read clean but return wrong or expensive results Who this is for Practitioners with at least 2 years of analytics engineering or SQL heavy analytics work Experts in SQL across joins, window functions, CTEs, and query optimization Builders with hands on experience in a modern warehouse such as BigQuery, Snowflake, or Redshift Clear writers who can document the reasoning behind a data modeling decision Contract and pay $60 to $100/hr , paid weekly via Stripe. Your rate is set from your experience, not negotiated down after you start. Fully remote, fully async. No fixed hours. Minimum 10 hours per week, no maximum. Scale up or down week to week. No screen recording, no keystroke monitoring, no idle timers. Independent contractor. Ongoing project work rather than single task batches. How our hiring process works Apply at /apply/sql-analytics-engineer-expert. About five minutes. Resume plus a few structured questions. Resume review. Every application gets read against a published rubric and gets a decision. Written assessment. You may be asked to take a written assessment for further placement. Onboarding. Sign the contractor agreement, connect Stripe, and get platform access. Project match. You're matched to live work in your specialty, usually within a week of onboarding. About AfterQuery AfterQuery is an expert data lab. We build the evaluation and training data that frontier AI labs use to measure what their models can and can't do in real professional work. Our contributors are practicing professionals, not annotators, and the work is credited, reviewed, and paid at professional rates.