Lead Data Engineer

Lead Data Engineer

Location:

US

The Lead Data Engineer is a senior, hands‑on technical leader responsible for owning and shaping KCI’s enterprise data foundation, with a strong emphasis on Dynamics 365 Finance & Operations (D365 FO) and Dataverse / Project Operations. The role ensures ERP and operational data is accurately modeled, governed, and made analytics‑ and AI‑ready for Power BI and emerging use cases.

• Serve as the technical owner for enterprise data engineering related to D365 FO, Dataverse / Project Operations, and related operational systems.
• Bring deep ERP expertise to eliminate ambiguity and ensure data is sourced, transformed, and represented correctly.
• Design, build, and maintain scalable data pipelines that stage, transform, and curate ERP and operational data for analytics and AI.
• Design and own the semantic data layer including SQL views, reusable curated datasets, and gold‑layer models that developers and report builders consume; raw ERP tables are not accessed directly without a governed abstraction layer.
• Establish and govern modern data architecture patterns such as medallion layers (bronze, silver, gold).
• Partner closely with ERP developers and Power BI / report developers to ensure enterprise data is consistently modeled, performant, and analytics‑ready.
• Act as the dedicated data enablement resource for Power BI and report developers, proactively surfacing available datasets, documenting common reporting tables and fields, and ensuring developers have what they need.
• Enable AI and solution teams by providing trusted, well‑curated data assets suitable for experimentation and production use.
• Collaborate with the Data Operations Manager to align ingestion processes, data quality checks, monitoring, and operational support.
• Own a living enterprise data dictionary and catalog covering the most commonly used D365 FO and Dataverse tables, fields, domains, data lineage, refresh paths, and semantic meaning.
• Establish practical standards for SQL development, data modeling, testing, and deployment.
• Provide hands‑on technical leadership and set direction without direct people management.
• Translate analytics and AI needs into clear, executable data designs grounded in ERP reality.
• Communicate data risks, dependencies, and opportunities to leadership.
• Perform other duties as assigned.

• Bachelor’s degree in a technical or analytical field, or equivalent experience.
• 7+ years of experience in data engineering, analytics engineering, or enterprise data platforms.
• Deep, hands‑on experience with ERP data, specifically Dynamics 365 Finance & Operations (Dataverse / Project Operations strongly preferred).
• Advanced SQL expertise, including complex transformations, performance tuning, data validation, and design of reusable SQL views and semantic models.
• Experience enabling Power BI and report developers with well‑modeled, documented datasets and the ability to explain data structure, field definitions, and join logic.
• Strong understanding of data modeling for analytics and reporting.
• Proven ability to document complex data structures clearly and accurately.
• Ownership mindset with the ability to lead through expertise and influence.
• Experience with cloud data platforms such as Azure Synapse, Azure Data Factory, or Microsoft Fabric (preferred).
• Familiarity with Python or similar languages for data processing or orchestration (preferred).
• Exposure to AI or machine‑learning initiatives from a data enablement perspective (preferred).
• Experience contributing to data governance, lineage, or cataloging efforts (preferred).
• Microsoft certifications in data engineering, analytics, or enterprise application architecture (e.g., Azure Data Engineer, Fabric Analytics Engineer, or Dynamics 365 Finance & Operations) (preferred).
• Pre‑employment drug screening and background check are conditions of employment. Motor vehicle checks may be required based on position.

KCI Technologies, Inc. is an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.