Senior Data Engineer (Modern Data Stack) [Only Canada]

At Tekton Labs, a technology outsourcing company with presence in Peru, Mexico, and the USA, we are looking for a Senior Data Engineer to join our team and collaborate directly with our client in the Canadian financial sector.

Offer: Contractor: USD 2500.00

Timezone: (UTC-04:00) Ottawa, Canada - Eastern Daylight Time (EDT)

English Level: C1 - Advanced

Spanish Level: C2 - Native

Responsibilities

Key Responsibilities

• Design and build scalable, robust data models in Snowflake to support diverse analytics and reporting needs.
• Build and maintain modular, tested, and well-documented ELT/ETL pipelines using dbt.
• Design complex workflow orchestrations and dependency graphs in Dagster or Apache Airflow, ensuring high availability and fault tolerance.
• Write clean, efficient, and reusable Python code for data functions, pipeline development, and data asset monitoring.
• Leverage cloud services (AWS and Azure) to manage data lake storage, compute resources, and secure data sharing.
• Implement automated testing and continuous deployment via CI/CD with GitHub Actions.
• Manage infrastructure as code with Terraform where applicable.
• Conduct code reviews and champion software engineering best practices within the data team (version control, testing, documentation).
• Protect PII and sensitive data across all pipelines and environments.

Must Have

• Location & Work Authorization: Must reside in Canada, hold valid Canadian work authorization, and be available to work 2 days per week onsite in Vancouver, Calgary, or Toronto.
• Experience: 5+ years in data engineering, software engineering, or a related quantitative field, with data pipelines running in production.
• Snowflake: Deep understanding of internal architecture (virtual warehouses, clustering, micro-partitioning, Snowpipe, and cost optimization).
• dbt: Proven track record running dbt in production at scale.
• Orchestration: Strong production experience with Dagster or Apache Airflow (custom operators, sensors, software-defined assets).
• Advanced Python: Solid proficiency with libraries such as pandas, pytest, and package/environment management with poetry or pipenv.
• Advanced SQL: Writing highly optimized and complex queries, as well as data modeling for analytics.
• Cloud & DevOps: Hands-on experience with AWS (S3, IAM) or Azure, Git version control, CI/CD (GitHub Actions), Terraform, and observability tools such as Datadog.
• Data Governance & Privacy: Working knowledge of data privacy standards, security, and PII handling.
• Communication: Clear written and spoken English for daily cross-functional collaboration with Tech Leads, analysts, and product teams.

Nice to Have

• Experience within banking, fintech, or other highly regulated environments.
• Hands-on experience with both Dagster and Airflow, or multi-cloud exposure (AWS and Azure / GCP).
• Experience with data contracts, schema validation, and data quality testing frameworks (dbt tests, Great Expectations, or Soda).
• Experience mentoring other data engineers.