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 workflowsdefining 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 DBTCortex 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
- 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.
Contract and Payment Terms
- You will be engaged as an independent contractor.
- This is a fully remote role that can be completed on your own schedule.
- Projects can be extended, shortened, or concluded early depending on needs and performance.
- Your work will not involve access to confidential or proprietary information from any employer, client, or institution.
- Payments are weekly on Stripe or Wise based on services rendered.
Skills: ml,data engineering,datasets,snowflake,dbt,panda,data,spark,pandas,python,etl,airflow,research,sql
