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4 дня назад

Senior Data Engineer (Snowflake)

100 000 - 135 000CAD
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Canada
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Senior Data Engineer (Snowflake/dbt): Building governed lakehouse data products and production pipelines for analytics, AI, and customer-facing dashboards with an accent on Snowflake performance, modular dbt models, and reliable data contracts. Focus on modernizing legacy ETL into streaming and incremental pipelines, implementing data quality and lineage, and designing reusable platform patterns for self-service data products.

Location: Hybrid in Montreal, Canada

Salary: $100,000–$135,000 CAD annual base salary or OTE

Company

hirify.global provides a subscription commerce platform that enables organizations to sell products and services through multiple channels and devices.

What you will do

  • Design, build, and evolve governed lakehouse platforms, reusable data models, and production pipelines using Snowflake, dbt, and Databricks.
  • Translate product and business requirements into data models and pipelines in partnership with product managers, business units, and engineers.
  • Modernize legacy ETL processes into efficient streaming and incremental pipelines.
  • Operate and optimize Snowflake for reliability, performance, warehouse utilization, and cost efficiency.
  • Build data products supporting analytics, internal dashboards, reporting services, App Insights, and other customer-facing experiences.
  • Improve data trust through governance, automated testing, validation, lineage, metadata management, documentation, and proof-of-concept research.

Requirements

  • 2+ years of production experience building and operating Snowflake data pipelines and models with SQL, Python, and dbt.
  • 2+ years of hands-on experience creating modular, version-controlled, tested dbt models using software engineering practices.
  • 2+ years of experience with AWS cloud services.
  • Strong understanding of data quality, lineage, validation, and data governance.
  • Experience with AI-assisted development tools and spec-driven development workflows.
  • Ability to communicate complex technical concepts, gather requirements, and collaborate effectively in a distributed team.

Nice to have

  • Hands-on experience with Databricks, Spark SQL or PySpark, and Delta Lake.
  • Experience with Fivetran or similar managed ELT connectors.
  • Exposure to Cube.dev or another semantic and metrics layer.
  • Experience building real-time data solutions with Apache Kafka.

Culture & Benefits

  • Values-driven culture focused on inclusion, individuality, and enabling people to do their best work.
  • Regular employees may be eligible for performance-based bonuses.
  • Full range of employee benefits is available.
  • Commitment to diversity and inclusion across race, religion, age, sexual orientation, gender identity, disability, and other intersecting identities.

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