HR Data Engineer (CAN)

Job Summary

Temporary, project-focused data engineering role within Location Operational Services (LOS), reporting to LOS Manager. Supports strategic transformation of local people analytics infrastructure following an organizational restructure that disrupted legacy analytics systems. This role thrives in constrained, transitional settings with sparse documentation and requires strong communication, documentation habits, and commitment to maintainable solutions. Prior HR/people data experience or sensitive data handling is essential, and comfort with ambiguity, pragmatic trade-offs, and close collaborative work is critical during this fast-paced 2-month engagement with extension potential.

Key Responsibilities

Primary Deliverable: Mandatory Training Dashboard Migration

• Migrate Mandatory Training Dashboard that tracks compliance training completion across organizational units; critical for audit and regulatory compliance
• Manage current pipeline components: manual Excel exports from Cornerstone (training data), organization-controlled Power BI report (employee master data 1), and SuccessFactors (employee master data 2), along with Access macros/VBA transformations, Power BI visualization, and Excel VB email processes

Migration Goals:

• Rebuild entire pipeline in Power Query (M language) on Power BI Fabric (gen2 dataflows, lakehouses)
• Implement resilient source switching with seamless failover if semi-automated exports fail
• Simplify and document logic for non-technical maintainers
• Execute parallel development with current solution remaining operational during migration

Core Technical Tasks:

• Reverse-engineer legacy Access macros, VBA, SQL, and Python to extract business logic
• Design and build Power Query dataflows replicating and improving existing transformations
• Implement data quality validation ensuring migrated solution matches legacy outputs
• Configure multi-source ingestion with upstream failure handling
• Document transformations through data dictionaries, process maps, and logic documentation
• Work with data sources including SuccessFactors, Cornerstone, and global organization-owned Power BI reports (all static Excel exports via SharePoint; no API connectors); Power BI datasets occasionally exported to Excel (fragile)

Required Skills

• SQL (Intermediate): Write and optimize joins, aggregations, subqueries, and CTEs; reverse-engineer complex queries; translate SQL logic to Power Query
• Python (Intermediate): Read and understand pandas data manipulation scripts; interpret existing Python ETL workflows (does not need to write production Python)
• Power Query (M Language – Foundational): Minimum awareness with willingness to learn quickly under guidance; strong SQL background enables effective on-the-job learning; must commit to building exclusively in Power Query (no SQL/Python/Access) for long-term maintainability
• Data Modeling (Strong Dimensional Modeling): Deep star schema understanding; experience with slowly changing dimensions, bridge tables, and role-playing dimensions; design models optimized for Power BI and DAX
• Power BI Fabric (Required): Hands-on experience with Fabric workspaces, gen2 dataflows, and lakehouses; understanding of Fabric-specific features and differences from gen1 environments; non-negotiable for 2-month delivery timeline
• Microsoft Access (Reverse-Engineering): Navigate and interpret Access databases (tables, queries, macros); understand Access design patterns; extract business logic for migration (no need to build new Access solutions)
• SharePoint (Data Storage/File-Based ETL): Experience using SharePoint as analytics data layer; comfortable with file-based workflows (Excel export ingestion, file path dependencies, refresh schedules)
• Data Quality & Documentation: Strong validation and reconciliation instincts; commitment to clear, accessible documentation for non-technical audiences
• Strong communication and documentation habits
• Commitment to pragmatic solutions and close collaborative work

Required Experience

• Prior HR or people analytics data experience essential
• Experience handling sensitive data essential
• Comfortable working in constrained, transitional settings with sparse documentation

Work Environment / Physical Requirements

• On-site requirement: 2 days per week in Burlington office
• Fast-paced, 2-month engagement requiring close collaboration and responsiveness
• Comfortable with ambiguity and pragmatic trade-offs

Benefits

• Medical insurance
• Vision insurance
• Dental insurance
• 401k Retirement Fund