Data engineer [h1.location_city]

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.