Senior Data Engineer - Snowflake DB

Description :

Role Description :

In this role, you will build and scale Snowflake-native data and ML pipelines, leveraging Cortexs emerging AI/ML capabilities while maintaining production-grade DBT transformations. You will work closely with data engineering, analytics, and ML teams to prototype, operationalize, and optimize 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.

Position : Senior Data Engineer

Job Type : Part-time (contractual)

Pay : $35 to $70 per hour

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.