Data Engineer, Microsoft Fabric
Armstrong Collective · Vancouver, British Columbia, Canada ·
- Work mode
- Hybrid
- Category
- Data engineering
- Experience
- 5+ years
Armstrong Collective · Vancouver, British Columbia, Canada ·
Purpose
The position reports to Senior Manager, Data Operations.
We are looking for a versatile Data Engineer with deep expertise across the Microsoft Fabric platform, spanning Real-Time Intelligence, Lakehouse, Spark engineering, Power BI semantic modelling, and enterprise data modelling. This is a hands-on individual contributor role focused on designing, building, and operating modern data solutions end-to-end.
In this role, you will take ownership for delivering reliable, well-governed data products that support operational and strategic decision-making. You will apply sound judgment, collaborate closely with partners, and continuously develop your technical expertise while contributing to a high-performing data engineering team.
Key Responsibilities
• Design and maintain canonical data models that serve as the foundation for analytics, reporting, and data products.
• Build and operate scalable batch and streaming data pipelines using Microsoft Fabric Real-Time Intelligence and Lakehouse capabilities.
• Develop, optimize, and maintain KQL queries, functions, update policies, and materialized views for real-time data processing.
• Build and maintain Spark and PySpark pipelines using medallion architecture and Delta Lake best practices.
• Modernize legacy T-SQL stored procedures and SQL workloads into Spark-based solutions, ensuring accuracy and maintainability.
• Design and maintain Power BI semantic models aligned to enterprise data models and business requirements.
• Apply data governance practices using Microsoft Purview, including cataloguing, lineage, classification, and responsible data handling.
• Monitor data pipelines, proactively identify issues, and take ownership for data quality, reliability, and performance.
• Collaborate with architects, analysts, and business stakeholders to translate requirements into scalable, well-modelled data solutions.
• Contribute to data engineering standards, documentation, and continuous improvement initiatives.
Required Qualifications
• 5+ years of data engineering experience delivering both batch and streaming data solutions.
• Strong expertise in data modelling, including normalized and dimensional modelling techniques.
• Hands-on experience with Microsoft Fabric, including Real-Time Intelligence (Eventhouse/KQL) and Lakehouse/OneLake.
• Strong proficiency in KQL (Kusto Query Language) and Spark (PySpark and Spark SQL).
• Experience migrating complex SQL and T-SQL workloads to Spark-based platforms.
• Experience building Power BI semantic models and reports, including Direct Lake and DirectQuery.
• Familiarity with data governance and cataloguing using Microsoft Purview.
• Strong problem-solving skills, attention to detail, and a continuous learning mindset.
• Ability to communicate technical concepts clearly and collaborate effectively as an individual contributor.
Preferred Qualifications
• Microsoft certifications such as DP-700 (Fabric Data Engineer Associate), DP-600 (Fabric Analytics Engineer), DP-203, or Databricks Data Engineer Associate / Professional.
• Experience with Fabric IQ and Copilot-driven development across Fabric workloads.
• Experience with Data Activator for event-driven actions and alerting.
• Background implementing enterprise data governance frameworks (data quality, stewardship, lineage, role-based access) anchored in Purview.
• Exposure to Data Mesh architectures, medallion architecture, and lakehouse design patterns in addition to dimensional modelling.
• Experience working in regulated or data-sensitive industries (finance, healthcare, travel, etc.) where data quality and auditability are critical.
What Success Looks Like
You are a collaborative and dependable team member who works effectively with colleagues and approaches discussions with a respectful, supportive tone. You contribute to shared understanding by clearly explaining technical concepts and design decisions, and you are known for your reliability, sound judgment, and willingness to share knowledge to strengthen overall team capability.
Within the first 2 months: You take ownership of understanding our core business domains and actively contribute to the design of our canonical data model. You partner closely with architects, data engineers, and business SMEs to capture key entities, relationships, and business rules, and to produce conceptual, logical, and physical models that anchor our Microsoft Fabric platform.
Within 3 months: You are fully onboarded to our Fabric and Databricks environments and are independently contributing to existing KQL and PySpark codebases. You deliver meaningful improvements to at least one real-time or lakehouse pipeline, ensuring alignment with the canonical model and demonstrating accountability for quality and performance.
Within 6 months: You own one or more end-to-end data products spanning ingestion, Spark transformation, dimensional modelling, semantic modelling, and Power BI delivery. You take responsibility for migrating a significant set of T SQL stored procedures to Spark and consistently apply Purview-based governance practices, demonstrating pride in your work, attention to detail, and commitment to continuous improvement.
Work Environment
• Eligible to work in Canada
• Hybrid working arrangements with 3 days work from office.
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.
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