Data Engineer

Position Overview

The Data Engineer is responsible for designing, building, and maintaining the organization’s enterprise data pipelines, curated datasets, and analytics platform foundation. This role enables timely, accurate, and trusted decision-making by ensuring reliable, scalable, and governed data flows across the Enterprise Resource Planning (ERP) system, Product Lifecycle Management (PLM) system, and other integrated business applications.

Position Overview

The Data Engineer is responsible for designing, building, and maintaining the organization’s enterprise data pipelines, curated datasets, and analytics platform foundation. This role enables timely, accurate, and trusted decision-making by ensuring reliable, scalable, and governed data flows across the Enterprise Resource Planning (ERP) system, Product Lifecycle Management (PLM) system, and other integrated business applications.

The Data Engineer will engineer ingestion and curation from vendor-hosted enterprise data repositories and integration services, including Infor OS Data Lake and supported extraction methods (e.g., Data Fabric Objects API, Compass SQL API / Compass JDBC Driver, ION Data Lake Flows, and ETL Client for Data Lake). The role will enable enterprise analytics and reporting through Microsoft Fabric and Power BI, and will use Spark/PySpark, SQL, and Python to deliver performant, scalable transformations.

This role also supports the organization’s increasing use of AI-enabled analytics by preparing high-quality, well-governed datasets and following company requirements for responsible and compliant AI usage.



Key Job Responsibilities

Data Engineering & Architecture (Microsoft Fabric / Lakehouse)

• Design and maintain a modern enterprise analytics foundation using Microsoft Fabric (Lakehouse/Warehouse patterns) to support governed reporting and self-service analytics.
• Build and manage curated data layers aligned to medallion-style processing (raw → standardized → curated) using Spark/PySpark, SQL, and Python.
• Develop and maintain enterprise data models optimized for analytics performance, consistent KPI definitions, and reuse across business domains.

• Develop and support automated ingestion from Infor OS Data Lake using supported extraction/integration methods such as:
• Data Fabric Objects API (object/file extraction)
• Compass SQL API / Compass JDBC Driver (query-based extraction)
• ION Data Lake Flows (scheduled push to connection points)
• ETL Client for Data Lake (scheduled transfer patterns)
• Stream Pipelines where applicable for continuous/near real-time delivery
• Implement incremental loading patterns, orchestration, monitoring, alerting, and failure recovery to ensure reliable delivery of daily/near real-time datasets.
• Partner with application and integration teams to align ingestion with upstream interfaces, data contracts, and security requirements.

• Provide trusted, well-documented datasets that enable enterprise dashboards and self-service analytics in Power BI.
• Build and maintain business-friendly semantic/dimensional models that support high-performance dashboards and consistent KPI definitions.
• Support modernization and migration of reporting assets into Microsoft Fabric, ensuring datasets and models align to reporting needs and enterprise metric definitions.

• Implement validation, reconciliation, and anomaly detection to ensure accuracy and completeness of curated datasets.
• Establish automated checks for common data issues (duplicates, missing attributes, invalid statuses, inconsistent units of measure).
• Partner with master data stakeholders and business data stewards to define standards, drive adoption, and remediate root-cause issues impacting data quality.

• Prepare AI-ready datasets by ensuring data completeness, consistency, lineage, and documentation (e.g., feature-ready curated tables, standardized definitions, and auditability).
• Support AI-assisted development workflows (e.g., using copilots/assistants to…