Nova White

Mercor is partnering with a cutting-edge AI research lab to hire a Senior Data/Analytics Engineer with expertise across DBT and Snowflake’s Cortex CLI . In this role, you will build and scale Snowflake-native data and ML pipelines, leveraging Cortex’s emerging AI/ML capabilities while maintaining production-grade DBT transformations. You will work closely with data engineering, analytics, and ML teams to prototype, operationalise, and optimise AI-driven workflows—defining best practices for Snowflake-native feature engineering and model lifecycle management. This is a high-impact role within a modern, fully cloud-native data stack. Responsibilities Design, build, and maintain DBT models, macros, and tests following modular data modeling and semantic best practices. Integrate DBT workflows with Snowflake Cortex CLI , enabling: Feature engineering pipelines Model training & inference tasks Automated pipeline orchestration Monitoring and evaluation of Cortex-driven ML models Establish best practices for DBT–Cortex architecture and usage patterns . Collaborate with data scientists and ML engineers to produce Cortex workloads in Snowflake. Build and optimise CI/CD pipelines for dbt (GitHub Actions, GitLab, Azure DevOps). Tune Snowflake compute and queries for performance and cost efficiency . Troubleshoot issues across DBT arti-facts, Snowflake objects, lineage, and data quality. Provide guidance on DBT project governance, structure, documentation, and testing frameworks . Required Qualifications 3+ years experience with DBT Core or DBT Cloud , including macros, packages, testing, and deployments. Strong expertise with Snowflake (warehouses, tasks, streams, materialised views, performance tuning). Hands-on experience with Snowflake Cortex CLI , or strong ability to learn it quickly. Strong SQL skills; working familiarity with Python for scripting and DBT automation. Experience integrating DBT with orchestration tools (Airflow, Dagster, Prefect, etc.). Solid understanding of modern data engineering, ELT patterns, and version-controlled analytics development . Nice-to-Have Skills Prior experience operationalising ML workflows inside Snowflake . Familiarity with Snow-park , Python UDFs/UDTFs. Experience building semantic layers using DBT metrics. Knowledge of MLOps / DataOps best practices. Exposure to LLM workflows, vector search, and unstructured data pipelines . Why Join You will be an hourly contractor through Mercor , working 20–40 hours per week with flexibility. Direct opportunity to build next-generation Snowflake AI/ML systems with Cortex. High-impact ownership of DBT and Snowflake architecture across production pipelines. Work alongside top-tier ML engineers, data scientists, and research teams. Fully remote, high-autonomy environment focused on innovation, velocity, and engineering excellence. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.