Publié il y a 12 jours
Senior Data Engineer (Modern Data Stack) [Only Canada]
@ Tekton Labs
Canada
SIGNAUX
Résumé des exigences :
- 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 et dates
Type de source non vérifié · apify-linkedin
- Date publiée par l’employeur
- 2026-11-01
- Première détection par notre source
- 2026-11-14
- Mise à jour du dossier source
- 2026-11-14
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Tekton Labs
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 1 |
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
Must Have:
Nice to Have:
Apply by sending your resume and briefly tell us why you want to participate in this project 🚀
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.
Apply by sending your resume and briefly tell us why you want to participate in this project 🚀
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