Data & Analytics Engineer, MS Fabric
Armstrong Collective · Vancouver, British Columbia, Canada ·
- Work mode
- Hybrid
- Category
- Data analytics
- Experience
- 5+ years
- Visa sponsorship
- No
- Company size
- 51-200
- Salary
- CAD 105,000 – 125,000 / year
Armstrong Collective · Vancouver, British Columbia, Canada ·
Role Overview
Armstrong Collective is the parent company of Rocky Mountaineer and Canyon Spirit, creating unforgettable rail journeys through some of the most breathtaking landscapes in Western Canada and the American Southwest. Guided by our values—Create Meaningful Moments, Be One Team, and Achieve Extraordinary Outcomes, we show up every day with pride, ownership, and a shared commitment to excellence. We work hard, support one another, embrace new possibilities, and celebrate growth, all in a respectful and inclusive environment where integrity, collaboration, and passion for the guest experience lead the way.
We are looking for a versatile Data Engineer with deep expertise across the Microsoft Fabric platform who demonstrates strong ownership, accountability, and continuous learning while delivering modern data solutions end-to-end. In this individual contributor role with informal technical leadership expectations, you take initiative to guide approaches, influence best practices, and support peers, while remaining hands-on in design, build, and delivery.
You are responsible for ingesting high-volume data, designing canonical data models, modernizing legacy T-SQL workloads, modelling data in the Lakehouse, and delivering trusted analytics solutions. You proactively collaborate with stakeholders, align work to business outcomes, and contribute to advancing a governed, self-serve analytics ecosystem.
Key Responsibilities
• Design canonical data models, taking ownership of data quality, integrity, and alignment to business needs.
• Apply entity-relationship, normalized, and dimensional modelling techniques with strong attention to detail and continuous improvement.
• Design and implement end-to-end data pipelines, proactively identifying risks and ensuring reliability and scalability.
• Build and optimize Spark / PySpark pipelines, ensuring performance, maintainability, and quality outcomes.
• Lead the modernization of legacy T-SQL workloads into Spark, influencing design decisions and ensuring successful delivery.
• Design and maintain Power BI semantic models, enabling business-friendly and high-performing datasets.
• Build intuitive Power BI reports and dashboards that drive decision-making and user adoption.
• Champion self-serve analytics by enabling users, promoting best practices, and contributing to governance standards.
• Leverage Fabric and Copilot capabilities to improve productivity and generate insights.
• Implement monitoring, observability, and data quality controls, taking proactive action on issues.
• Collaborate with stakeholders, guiding discussions and clarifying requirements to deliver effective data solutions.
• Contribute to standards, CI/CD practices, and documentation, influencing continuous improvement across the team.
Experience and Qualifications
• 5+ years of data engineering experience with delivery of batch and streaming workloads.
• Strong Power BI development experience including semantic models, reports, dashboards, and advanced DAX.
• Demonstrated expertise in enterprise data modelling including ER, normalized, and ildimensional modelling.
• Experience designing canonical data models across multiple systems and use cases.
• Hands-on experience with Microsoft Fabric, Lakehouse, Pipelines, and Notebooks.
• Strong Spark / PySpark experience with production environments such as Databricks or Fabric.
• Experience converting complex T-SQL workloads into Spark with structured validation approaches.
• Strong T-SQL knowledge and understanding of relational systems.
• Experience with CI/CD practices, including source control and deployment pipelines.
• Experience supporting self-serve analytics and enabling business users.
• Proficiency with data modelling tools.
Preferred Qualifications
• Relevant Microsoft and data certifications (e.g., DP-700, DP-600, PL-300, DP-203, Databricks certifications).
• Experience with Fabric Copilot or AI-assisted development tools.
• Exposure to data mesh, medallion architecture, and modern data design patterns.
• Experience in regulated or data-sensitive industries.
What Success Looks Like
• Demonstrates strong ownership and accountability, consistently delivering high-quality data solutions.
• Builds trusted relationships and collaborates effectively across teams.
• Acts as a go-to technical contributor, proactively supporting and influencing others.
• Continuously improves systems, processes, and personal capability.
• Within first 2 months: contributes to canonical data model design and understands platform architecture.
• Within 3 months: delivers enhancements to pipelines and publishes semantic models and reports.
• Within 6 months: owns end-to-end data products and contributes to migration and governance initiatives.
What Success Looks Like
• Demonstrates strong ownership and accountability, consistently delivering high-quality data solutions.
• Builds trusted relationships and collaborates effectively across teams.
• Acts as a go-to technical contributor, proactively supporting and influencing others.
• Continuously improves systems, processes, and personal capability.
• Within first 2 months: contributes to canonical data model design and understands platform architecture.
• Within 3 months: delivers enhancements to pipelines and publishes semantic models and reports.
• Within 6 months: owns end-to-end data products and contributes to migration and governance initiatives.
Work Environment
Compensation
Eligible Benefits
Armstrong Collective supports our team members’ health and wellness by providing a comprehensive medical plan with 100% employer paid premiums, some of which includes:
Armstrong Collective, Rocky Mountaineer and Canyon Spirit are an equal opportunity employer, driven by our values of creating meaningful moments, being one team, and achieving extraordinary outcomes. Our strong company culture supports our vision of a diverse, open, safe, and respectful workplace. We celebrate diversity and are committed to creating an inclusive environment for all team members. If you require any accommodation during the application process or throughout your employment, please let us know. We will work with you to ensure your needs are met and to create a supportive environment.