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Posted 12 days ago

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

@ Tekton Labs

Canada

Full-time
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SIGNALS

Requirements summary:

  • 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.
  • Orchestration: Strong production experience with Dagster or Apache Airflow (custom operators, sensors, software-defined assets).
  • 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.
  • 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).
Source and dates

Source type not verified · apify-linkedin

Employer posting date
2026-11-01
First seen by our source
2026-11-14
Source record updated
2026-11-14

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Tekton Labs

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Job description
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:

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:

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.

💡 Are you interested in this opportunity?

Apply by sending your resume and briefly tell us why you want to participate in this project 🚀

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