Data Engineer & Operations Specialist

Hybrid Data Engineer & Operations Specialist to build reliable reporting pipelines and support operational administration across a multi-site retail environment.

Responsibilities

• Build and maintain repeatable data extracts from ERP, e-commerce, POS, payroll, and related systems
• Design and document ETL/ELT workflows with scheduling, dependencies, and failure monitoring
• Standardize store, product, brand, calendar, and employee data across multiple systems
• Monitor data pipelines, investigate errors, and resolve root causes independently
• Build and maintain Power BI semantic models, DAX measures, refresh schedules, and workspace governance
• Develop reporting for sales, store performance, labor productivity, inventory movement, and brand/category performance
• Replace manual spreadsheet reporting with governed, refreshable dashboards
• Deliver ad hoc analysis with clear assumptions, caveats, and executive-friendly summaries
• Reconcile reporting outputs back to source systems and document known variances
• Maintain data dictionaries, calculation logic, source-of-truth definitions, and refresh schedules
• Establish appropriate access controls for sensitive financial, labor, and sales data
• Identify unreliable or incomplete data, escalate issues early, and prevent inaccurate publishing

Operations Administration (Facilities and Lease Support)

• Manage intake, triage, and prioritization of store maintenance and facilities requests
• Coordinate vendors, quotes, scheduling, completion verification, and maintenance records
• Maintain accurate facilities tickets, including status, cost, vendor details, and resolution notes
• Escalate safety, customer-experience, and budget-sensitive issues through appropriate channels
• Maintain lease abstracts, key terms, rent schedules, and document records in lease administration systems
• Track renewals, escalation dates, option windows, CAM reconciliations, and other lease milestones
• Support landlord and property-manager communication while maintaining accurate decision records
• Reconcile lease-related costs against accounting records and flag discrepancies
• Communicate proactively with U.S.-based stakeholders regarding risks, dependencies, reporting issues, and operational priorities
• Balance analytical project delivery with operational requests while protecting the reporting roadmap and data quality

Requirements

• 5+ years of experience in data engineering, BI development, analytics, or a closely related field
• Strong hands-on Power BI experience, including semantic modeling, DAX, refresh management, and workspace governance
• Strong SQL skills
• Practical experience building and maintaining scheduled data pipelines using Python, Power Query, Azure Data Factory, or comparable tools
• Experience integrating data from ERP, e-commerce, POS, or other operational systems
• Experience working with REST APIs, including authentication, pagination, and scheduled ingestion
• Strong analytical, troubleshooting, and root-cause analysis skills
• Excellent written and verbal English
• Ability to work independently and communicate effectively with U.S.-based stakeholders
• Strong attention to data quality, documentation, and reporting accuracy
• Updated Resume/CV
• Ability to work in a fast-paced, dynamic environment
• Reliable internet connection and a personal computer
• UPS/battery backup to ensure continuity during power interruptions

Technologies

• Power BI, DAX, SQL, ETL/ELT
• Python, Power Query, Azure Data Factory, REST APIs
• ERP, e-commerce, POS
• Power BI semantic models
• NetSuite, Shopify
• MRI ProLease, Microsoft Fabric
• dbt

Benefits

• Competitive salary with performance-based incentives
• WFH set-up
• Opportunities for career advancement
• HMO coverage for employee and immediate family members

Strongly Preferred

• Experience with NetSuite and Shopify
• Experience with MRI ProLease or comparable lease administration software
• Experience in retail, e-commerce, or multi-site operations
• Familiarity with retail metrics such as sell-through, units per transaction, labor productivity, and comparable-store performance
• Experience with Microsoft Fabric, Azure Data Factory, dbt, or similar modern data-stack tools
• Exposure to facilities, property, or multi-site operations
• Experience replacing spreadsheet-based reporting with governed BI dashboards