Senior Data Engineer to build Snowflake/dbt transformations and data pipelines
- Contractor
Duration: 3 months initially, with potential extension to 6 months
Location: Canada - Fully Remote
Start: ASAP
Job Description
Our Client, a National Beverage Distributor is building a modern Data & AI platform and is looking for a hands-on Senior Data Engineer to support an immediate increase in project demand.
This role is focused on development and execution rather than architecture or technical leadership. The successful candidate will work directly in Snowflake and dbt to build, enhance, and optimize scalable data transformations, pipelines, and data products supporting analytics and AI initiatives.
You will build and maintain layered dbt models across staging, curated, and domain-mart layers while working with SQL, Python, Airflow, AWS, and GitLab-based CI/CD processes.
Must-Have Requirements
- 5+ years of professional Data Engineering experience
- Strong recent hands-on production experience with dbt
- Strong hands-on Snowflake development experience
- Advanced SQL skills, including complex data transformations and data modeling
- Python experience for data transformation, automation, and pipeline support
- Experience building layered data models such as staging, curated, and dimensional/domain marts
- Experience with dbt models, tests, macros, snapshots, incremental logic, and documentation
- Experience with Airflow or similar data orchestration platforms
- Experience with Git and CI/CD pipelines, ideally GitLab
- AWS experience including S3, Lambda, and IAM
- Experience troubleshooting and optimizing production data pipelines
- Strong understanding of data quality, reliability, lineage, and governance
- Ability to work effectively in a fast-paced enterprise Data & AI environment
Responsibilities
- Build and maintain production dbt projects, including staging, curated, and domain-mart models
- Develop incremental models, snapshots, macros, reusable packages, and automated dbt tests
- Design dimensional and curated data models supporting analytics, reporting, and downstream applications
- Develop ELT transformations using dbt, advanced SQL, and Python
- Monitor and troubleshoot production data pipelines, data-quality issues, and failed jobs
- Implement source freshness checks, data testing, documentation, lineage, and governance standards
- Orchestrate dbt and related data workloads using Airflow
- Support ingestion and automation using AWS services including S3, Lambda, and IAM
- Optimize Snowflake queries, warehouse sizing, clustering, materializations, storage, and overall platform cost
- Build and maintain CI/CD workflows using Git and GitLab
- Participate in code reviews, automated testing, debugging, and continuous improvement of production data workflows
- Work closely with Data Engineering, Architecture, Analytics, AI, and other cross-functional teams
Nice to Have
- Experience optimizing Snowflake warehouse performance and cost
- Experience with data observability and data-quality platforms
- Experience working in large-scale enterprise environments
- Experience using AI-assisted development tools to improve engineering productivity and code quality
- Previous experience supporting analytics or AI data products