Master Data Engineer

Marco Technologies is hiring a Master Data Engineer to build and operate governed pipelines that maintain accurate, consistent master data across its ERP, CRM, and data warehouse systems. The role establishes data standards and ontology, leads data quality and governance workflows, and partners with business and technical teams to document and improve master data.

Responsibilities:

• Design, build, and maintain automated data pipelines (Microsoft Fabric Dataflows Gen2, notebooks/PySpark, SQL) that consolidate and reconcile master data across e-Automate, Salesforce, and Marco’s Fabric data warehouse
• Serve as the primary engineer and steward of core master data domains — customer, item/equipment, vendor, and location — ensuring pipelines enforce accuracy, completeness, and de-duplication at the source, not after the fact
• Define and enforce Marco’s formal data ontology, MDM standards, naming conventions, and business rules, implemented as automated validation and match/merge/survivorship logic within pipelines
• Partner with the data architecture team to model business concepts and real-world entity relationships, turning raw data into machine-readable, query able knowledge
• Lead recurring data quality audits and build automated profiling and reconciliation jobs across ERP, CRM, and Fabric repositories; engineer remediation workflows for ancillary data that lives outside core systems
• Build and maintain the intake and approval workflow for create/change/merge/deactivate requests on master records as a governed, auditable process, partnering with requesting departments to validate before load
• Document data governance standards, field definitions, lineage, and stewardship procedures in a living data dictionary; publish self-serve documentation that lets business users understand the data they use
• Partner with the BI/reporting function to catch master data quality issues via automated checks before they reach downstream dashboards and reports
• Train and support cross-functional teams (Sales, Service, Procurement, Finance) on master data intake standards and the technical and business impact of poor data quality
• Track and report data quality and pipeline KPIs (duplicate rate, completeness, accuracy, cycle time, pipeline SLA) to the Director of Enterprise Data and Analytics

Requirements:

• Bachelor's degree in computer science, information systems, or a related field, or equivalent practical experience
• 7+ years of experience in data engineering, master data management, or a related data-operations role, including experience setting standards or leading initiatives with minimal supervision
• Strong proficiency in Python (including PySpark) and SQL for pipeline development, data profiling, validation, and reconciliation
• Hands-on experience building and maintaining pipelines in Microsoft Fabric (Dataflows Gen2, notebooks, Lakehouse) or a comparable modern data platform (Databricks, Snowflake)
• Hands-on experience integrating MDM processes with ERP and/or CRM platforms (e-Automate, Salesforce, or comparable systems)
• Experience designing match/merge/survivorship logic and automated data quality rules
• Working familiarity with AI-assisted engineering tools (e.g., Claude, Copilot) for pipeline development and documentation
• Excellent attention to detail, documentation habits, and written/verbal communication with both technical and non-technical stakeholders
• Demonstrated ability to lead cross-functional data governance and engineering initiatives and influence stakeholders without formal authority