Senior Data Engineer Job at Randstad (Vancouver)

Job Description

We are seeking a highly technical, forward-thinking Senior Data Engineer / MLOps Platform Lead to pioneer the design, expansion, and optimization of our enterprise Machine Learning Operations (MLOps) ecosystem. In this role, you will serve as the definitive technical authority establishing global standards for infrastructure automation, pipeline orchestration, and system observability supporting the end-to-end machine learning model lifecycle. This position sits at the intersection of big data engineering, advanced cloud infrastructure architecture, and data science. You will simplify, standardize, and consolidate fragmented ML workflows across multiple cross-functional teams while ensuring the absolute reliability, security, and performance of our production cloud environments. Location: Vancouver, BC (Hybrid – 4 days per week onsite) Contract Duration: 6-month contract with high likelihood of extension

Job Responsibility

Define the enterprise standard architecture for MLOps, focusing on infrastructure scaling, automated continuous training (CT), and deployment observability
Consolidate and simplify disparate machine learning workflows across varied global data science teams into a unified platform
Build and scale robust ML/AI orchestration pipelines utilizing Databricks, Unity Catalog, and MLflow for model tracking, lineage tracking, and governance
Architect and manage secure enterprise cloud environments natively within Azure using Terraform for Infrastructure as Code (IaC)
Automate the provisioning of complex network configurations, cloud resources, IAM security privileges, and containerized configurations
Monitor cloud environment footprint performance, guaranteeing high availability, structural reliability, and cost optimization
Oversee and manage large-scale production deployments of batch and real-time machine learning models
Standardize the continuous integration and continuous delivery (CI/CD) pipelines utilizing Azure DevOps, Jenkins, or GitLab
Implement containerization and deployment orchestration frameworks across critical corporate data domains
Design and implement advanced telemetry, monitoring metrics, and proactive alerting frameworks for distributed cloud infrastructure and data apps
Act as the technical lead during critical system outages or customer escalations, orchestrating rapid incident resolution workflows and bridging communication across internal and external global vendors
Provide technical guidance, code review governance, and structured mentorship to intermediate and junior engineers

Requirements

4+ years of hands-on experience building, scaling, and maintaining production-grade MLOps pipelines using the Azure data ecosystem
3+ years of proven success building AI workflows specifically utilizing Databricks, Unity Catalog (for governance), and MLflow (for model tracking)
3+ years of documented experience in core Azure infrastructure management, networking boundaries, and secure enterprise provisioning
Expert-level proficiency in SQL, Spark SQL, Python, and PySpark data manipulation scripts
Proficient with Terraform (IaC), Apache Airflow, Azure Data Factory, Azure Functions, Snowflake, and Fabric OneLake environments
Demonstrated capability in active crisis management, handling customer escalations, and troubleshooting distributed runtime system failures
Bachelor’s degree in Computer Science, Software Engineering, or an equivalent technical field

Nice to have

Technical exposure to data architectures and machine learning tools across alternate cloud providers (AWS or GCP)
Prior experience delivering data platform engineering within the retail or digital e-commerce sector
Active certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Machine Learning Professional

What we offer

Strategic Architectural Influence: Build and define the net-new global standard for machine learning infrastructure for a premium corporate brand
Advanced Tech Spectrum: Work natively with cutting-edge data tech: Unity Catalog, serverless Azure frameworks, and modern IaC toolsets
Elite Collaboration Hub: Form part of an energetic, values-driven onsite workspace in Vancouver that fosters innovation and entrepreneurial spirit
Long-Term Program Depth: Secure an initial 6-month contract with highly probable rolling extensions as the global platform scales

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Senior Data Engineer

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