Backed by Insight and Pear VC.
About the role
We are looking for a Benchmark & Evaluation Engineer with a strong mix of data engineering, advanced SQL, and AI evaluation experience. You should have a "production data" sensibility—knowing how complex, messy, and multi-system enterprise environments operate—and a bias for rigor and honest scoring. By submitting your application to Expedock, you acknowledge and consent to the collection, use, and processing of your personal information for recruitment and hiring purposes. Your information will be used to: Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Advanced SQL & Data Modeling: Expert proficiency in production-grade SQL (CTEs, window functions, query plans, cardinality) and data modeling (star/snowflake schemas, SCDs, referential integrity)
- Data Engineering & Systems : Strong Python skills (pandas, NumPy, Polars) and hands-on experience standing up and loading data into at least one major warehouse (Snowflake, BigQuery, Redshift, or Postgres)
- Multi-System Data Environments : Ability to construct realistic multi-system setups (warehouses, data lakes, operational DBs, APIs) with large-scale, semi-structured, or dirty synthetic data
More about this role
Type: Part-time, hourly
Schedule: US Shift
About Expedock
We are a tech-enabled workforce augmentation platform leveraging top 1% offshore talent & cutting edge technology to enable businesses to unlock their full potential.
About the Client
Our client is an innovative AI platform company developing industry-standard benchmarks to evaluate how AI analysts handle complex, production-scale enterprise data. They are remote-first, fast-growing, and building products that bridge natural language analytics, data modeling, and end-to-end data systems.
Who We Need
We are looking for a Benchmark & Evaluation Engineer with a strong mix of data engineering, advanced SQL, and AI evaluation experience. You should have a "production data" sensibility—knowing how complex, messy, and multi-system enterprise environments operate—and a bias for rigor and honest scoring.
What You'll Do
- Build Realistic Data Environments : Design and stand up multi-system enterprise environments (warehouses, lakes, APIs, DBs) at scale across key domains like healthcare, finance, and product analytics.
- Engineer Benchmark Datasets : Generate calibrated, large-scale datasets with realistic noise, seasonality, drift,...
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