Data Engineer & Operations Specialist

Concertina is hiring a 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 documentation including data dictionaries, calculation logic, source-of-truth definitions, and refresh schedules.
• Establish and maintain access controls for sensitive financial, labor, and sales data.
• Identify unreliable or incomplete data and escalate issues before inaccurate information is published.
• 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 information, and resolution notes.
• Escalate safety, customer-experience, and budget-sensitive issues appropriately.
• Maintain lease abstracts, key terms, rent schedules, and document records within lease administration systems.
• Track renewals, escalation dates, option windows, CAM reconciliations, and other critical 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 work 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: 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.