Description
What you'll do
Mercor is partnering with leading AI labs to advance frontier agent evaluations in data engineering. As a Data Engineering Expert, you'll build long-horizon pipeline tasks that mirror the work you already do, each paired with a deterministic rubric that grades agent performance against verifiable ground truth. Tasks need to have checkable answers; no open-ended essays, no subjective judgment calls.
Expect to build scenarios across:
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Pipelines: ETL/ELT and dbt models that produce a specified output table, incremental logic with defined watermark behavior
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Orchestration and quality: Airflow/Dagster DAGs that pass a test suite, data quality tests with known pass/fail cases
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Warehouse design: schemas matching a defined contract, performance targets tied to a measured query-time budget
These scenarios will be challenging and take long sessions of focus.
Who we're looking for
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BS or MS in CS or related; 3+ years in data engineering or analytics engineering
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Expertise in one or more of the following: dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), data quality and testing
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Comfortable reading and producing data engineering artifacts: dbt models, DAGs, schema docs, data contracts, test suites
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Clear written communication; can articulate reasoning step by step and encode it into deterministic rubrics
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Located in the United States or Canada
Compensation
$90–$125/hr depending on domain depth and prior experience. Strong contributors are promoted based on task quality and throughput.
Interested in this position?
Apply directly on the company's website