Senior Engineer, Data

mSupply is North America’s leading distributor of OEM repair parts and equipment, serving professionals in various industries. The Senior Data Engineer designs, builds, and operates the enterprise data platform, ensuring pipeline reliability and data quality while collaborating with data scientists and engineers.

Responsibilities:

• Design, build, and maintain ELT/ETL pipelines that ingest data from ERP systems, operational tools, APIs, and third-party providers into Microsoft Fabric
• Own pipeline reliability and operational health across all medallion layers, ensuring data freshness, completeness, and accuracy
• Develop and maintain dbt models, tests, and documentation to enforce data quality standards and transformation traceability across the platform
• Build and optimize Fabric Pipelines, Notebooks, and Dataflows for orchestration, scheduling, error handling, and retry logic
• Monitor and troubleshoot pipeline failures, data quality anomalies, and performance bottlenecks with proactive alerting and observability
• Collaborate with Data Scientists and ML/AI Engineers to build and maintain feature pipelines and curated Gold layer datasets
• Support new source system onboarding as the company acquires new business units, developing repeatable ingestion patterns that accelerate time-to-value
• Implement and maintain CI/CD pipelines for dbt and Fabric workloads, including version control, automated testing, and deployment automation
• Optimize query performance, storage costs, and compute utilization across the Fabric environment

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience
• 5+ years of experience in data engineering, analytics engineering, or data platform roles with production pipeline ownership
• Strong proficiency in SQL and Python for data transformation, pipeline development, and automation
• Hands-on experience with modern ELT/ETL frameworks and data transformation tools such as dbt
• Experience designing and operating data pipelines in cloud-based environments (Azure, AWS, or GCP)
• Solid understanding of data modeling concepts, dimensional modeling, and medallion or multi-layer data architectures
• Experience with version control (Git), CI/CD practices, and automated testing for data workloads
• Experience with Microsoft Fabric, Azure Synapse Analytics, or Azure Data Factory
• Familiarity with Power BI, Direct Lake, SQL Analytics Endpoints, and OneLake
• Experience integrating data from ERP systems (Eclipse, Business Central, or similar) and operational platforms (ServiceTitan or similar)
• Background in wholesale distribution, supply chain, HVAC, plumbing, or related B2B sectors
• Experience or demonstrated ability using AI-powered tools (e.g., code assistants, LLMs, AI-augmented workflows) to accelerate work and improve outcomes