Data Engineer

Company Description

Crown Equipment Corporation is a leading innovator in world-class forklift and material handling equipment and technology. As one of the world’s largest lift truck manufacturers, we are committed to providing the customer with the safest, most efficient and ergonomic lift truck possible to lower their total cost of ownership.

Location:

New Bremen, OH, US, 45869

Company Description

Crown Equipment Corporation is a leading innovator in world-class forklift and material handling equipment and technology. As one of the world’s largest lift truck manufacturers, we are committed to providing the customer with the safest, most efficient and ergonomic lift truck possible to lower their total cost of ownership.

Job Posting External

Primary Responsibilities

• Design, develop, and support scalable enterprise data solutions on the Microsoft Fabric platform, leveraging Lakehouse, Data Warehouse, OneLake, Data Factory, Real-Time Analytics, and Power BI.
• Develop and optimize ETL/ELT data pipelines using Microsoft Fabric Data Factory, Notebooks, Dataflows Gen2, Pipelines, Event Streams, and streaming ingestion frameworks.
• Build high-performance data transformation frameworks using PySpark and Spark SQL within Fabric Notebooks to process large-scale structured and unstructured datasets.
• Design, develop, and maintain Lakehouse architectures, medallion data models (Bronze, Silver, Gold), and enterprise data products that support analytics, reporting, and AI use cases.
• Develop and optimize complex SQL queries, stored procedures, views, and data models within Fabric Data Warehouse and Lakehouse environments.
• Design and implement semantic models in Power BI, ensuring efficient data modeling, performance optimization, governance, and reusability across business domains.
• Develop enterprise-grade Power BI solutions, including DAX measures, calculated columns, Power Query (M) transformations, row-level security (RLS), and advanced dashboard visualizations.
• Collaborate with Business Analysts, Data Analysts, and stakeholders to gather requirements and translate business needs into scalable Fabric-based data solutions.
• Implement and support CI/CD, DevOps, and deployment automation using Git integration, deployment pipelines, source control, and environment promotion strategies.
• Establish data quality, data governance, lineage, security, and monitoring standards across Fabric workloads to ensure reliable and trusted data assets.
• Optimize Spark jobs, semantic models, and Power BI datasets for performance, scalability, and cost efficiency.
• Perform peer code reviews and enforce best practices for PySpark, SQL, Power BI, and Fabric development standards.
• Develop and maintain technical documentation, architecture diagrams, data flow mappings, and operational procedures in alignment with enterprise standards.
• Support real-time and near real-time data integration using technologies such as CDC, Kafka, Event Streams, APIs, and Fabric Real-Time Analytics.
• Work closely with QA and testing teams to develop unit tests, integration tests, and data reconciliation processes, ensuring solution quality and reliability.
• Provide production support, root cause analysis, performance tuning, and troubleshooting of Fabric pipelines, notebooks, semantic models, and reporting solutions.

Minimum Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Information Technology, Engineering, Mathematics, or a related technical field.

Strong expertise in PySpark and Spark SQL for large-scale data processing, transformation, and optimization.

Strong Experience Developing Enterprise-grade Power BI Solutions Including

• Semantic Models
• DAX Measures
• Power Query (M)
• Row-Level Security (RLS)
• Performance Optimization
• Interactive Dashboards and Reports

Preferred Qualifications

Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).

Microsoft Certified: Azure Data Engineer Associate (DP-203).

Experience with Real-Time Analytics, Eventhouse, KQL, and streaming data architectures.

Experience integrating SAP, Quipware, IFS, WMS, Manufacturing, Finance, or Supply Chain data into modern analytics platforms.

This position