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Randstad Logo Randstad · IT - Software Development

Data Engineer

Canada, Vancouver 46.22 - 61.63 CAD / Hour · Job Posted May 30, 2026
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Job Description

We are seeking a highly technical, delivery-focused Data Engineer with a specialized passion for data quality automation and infrastructure optimization. In this role, you will be responsible for the integration, multi-dimensional modeling, and orchestration of complex, large-scale data environments hosted natively on Snowflake and Databricks. This position sits at the intersection of core data platform engineering and data governance. Beyond building resilient data pipelines, you will design and implement custom, reusable automation testing frameworks to certify data quality across critical data domains. If you are an autonomous self-starter who loves digging deep into execution logs, profiling data lineage, and optimizing distributed data system queries, this role offers an exceptional playground for your skills. Location: Vancouver, BC (Hybrid – 4 days per week onsite) Contract Duration: 6-month contract with a high likelihood of extension

Job Responsibility

  • Identify, design, and implement end-to-end integration, structural data modeling, and data warehousing solutions
  • Build and scale robust ETL/ELT pipelines to process large-scale, complex datasets hosted across Snowflake and Databricks platforms
  • Monitor, isolate, and troubleshoot active data engineering incidents and transactional pipeline anomalies in runtime environments
  • Design and implement comprehensive data quality solutions for streaming and batch pipelines, ensuring complete adherence to enterprise data standards
  • Develop custom, reusable automated testing frameworks to validate data freshness, schema consistency, and accuracy across critical business domains
  • Act as an internal evangelist: educate, enable, and onboard cross-functional technical teams onto centralized data quality toolsets while enforcing industry best practices
  • Debug complex, distributed data processing systems using runtime logs, execution profiles, and end-to-end data lineage tracking to isolate root causes of technical debt
  • Optimize the compute performance of complex SQL queries, Spark jobs, and cloud data pipelines
  • Implement storage optimization strategies within structural architectural constraints to lower platform compute costs
  • Partner with Data Architects, Solution Deliverers, and Product Managers to define data quality requirements, evaluate technical feasibility, formulate effort estimations, and outline project scopes
  • Author and maintain high-quality technical documentation, process maps, and runbooks to support long-term operational maintainability

Requirements

  • 4–7 years of proven, hands-on experience as a Data Engineer, Big Data Developer, or in a closely related technical delivery role
  • Direct, operational experience utilizing Databricks, PySpark, and Snowflake data platforms
  • High proficiency in SQL paired with strong programmatic capabilities in Python (preferred), Java, or Scala
  • Extensive experience leveraging Azure Cloud Services (Azure Data Factory, Azure Functions, AKS, Docker)
  • Practical experience with data orchestrators (Apache Airflow or Azure Data Factory) and continuous integration pipelines (Jenkins, Azure DevOps, or GitLab)
  • Deep conceptual understanding of data management fundamentals, storage paradigms, star/snowflake schemas, and distributed data architectures
  • Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field

Nice to have

  • Direct technical experience working within the Retail or E-commerce domain is highly preferred
  • An inherently curious, self-directed analytical approach with a drive to uncover exactly why systems behave a certain way
  • High transparency and clarity in writing technical specifications and communicating complex data risks to multi-disciplinary teams

What we offer

  • Cutting-Edge Stack Control: Take direct technical ownership over an advanced modern cloud data stack combining Databricks clusters and Snowflake endpoints
  • High-Impact Architecture: Build a net-new automated data quality framework that will protect data integrity across a growing global organization
  • Strong Potential for Longevity: Step into an initial 6-month contract with highly anticipated extensions as the data engineering ecosystem continues to expand
  • Premium Collaborative Culture: Work out of a highly creative, values-led, and people-first onsite workspace in beautiful Vancouver
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