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Arc'teryx Equipment

High-performance outdoor apparel and gear

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
ContractNorth Vancouver, BC, Canada

About the Job

Requirements

  • Five to eight years of experience in data engineering, with expertise in cloud platforms (Azure preferred) and modern tools such as Databricks and PySpark.
  • Advanced SQL and Python skills, with hands-on experience in large-scale ETL/ELT, data lakes, and NoSQL databases such as Cosmos DB.
  • A proven track record in optimizing pipelines, implementing governance, and leading system migrations.
  • Strong knowledge of DevOps practices (CI/CD), data mesh concepts, and dimensional modeling.
  • Experience mentoring teams, leading architecture reviews, and influencing technical roadmaps.
  • Ability to communicate complex technical strategies to stakeholders and executives.
  • Passion for outdoor adventures and alignment with Arc’teryx’s values of sustainability and innovation.

Responsibilities

  • Design and implement scalable data architectures (batch/streaming, lakehouse) using Azure Databricks and PySpark.
  • Lead migrations from legacy systems to cloud-native platforms, ensuring minimal downtime and maximum performance.
  • Advocate for data mesh principles and dimensional modeling best practices.
  • Optimize ETL/ELT workflows for structured and semi-structured data, including Cosmos DB integrations.
  • Establish data quality frameworks, monitoring systems, and governance policies aligned with compliance standards.
  • Partner with SecOps/FinOps teams to enforce security protocols and cost controls.
  • Mentor junior engineers through code reviews, technical workshops, and hands-on guidance.
  • Lead cross-functional design reviews and backlog prioritization for critical initiatives.
  • Evaluate emerging tools, including GenAI pipelines and real-time processing, and drive proof-of-concept projects.
  • Lead the implementation of data mesh architecture across the organization.
  • Design advanced data quality and observability frameworks to ensure data reliability.
  • Establish enterprise-wide data governance standards and implementation patterns.
  • Create automated tooling for self-service data infrastructure provisioning.
  • Mentor junior engineers and shape the technical culture of the data organization.
  • Build specialized data processing solutions for complex business domains.
  • Optimize cloud infrastructure for performance, cost, and sustainability.
  • Collaborate with data scientists to enable ML-ready datasets and real-time analytics.
  • Define CI/CD workflows, infrastructure-as-code (Terraform), and SDLC best practices.

About the Company

Arc'teryx Equipment

High-performance outdoor apparel and gear

Arc’teryx designs and sells premium outdoor clothing and gear for activities like mountain running, hiking, and climbing. Its product range includes jackets, pants, footwear, and accessories for men and women, sold through its website, own stores, and selected outdoor retailers. The gear emphasizes technical performance and durable materials to perform in extreme conditions, with seasonal launches such as lighter mountain-running gear. The company differentiates itself through meticulous design, advanced materials, and a direct-to-consumer plus wholesale model, paired with a strong reputation for quality. Its goal is to equip adventure enthusiasts with reliable, high-performance equipment and to foster a sense of community around outdoor activity, as seen in initiatives like Muslim Hikers.

Company size
1,001-5,000
Company stage
M&A
Total funding
Not listed
Headquarters
Vancouver, Canada
Founded
1989

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