Data Engineer - Data Services

Job Posting External

Primary Responsibilities

• Analyze and evaluate existing or proposed systems and develop computer applications, systems, and related procedures.  
• Prepare program specifications, encode, test, and debug computer applications.
• Design, code, test, debug, install, document and maintain computer applications. 
• Participate in peer code reviews to uphold coding standards. 
• Create APIs to integrate between existing systems and customer applications.            
• Interface with users to extract functional needs and determine requirements. 
• Conduct detailed systems analysis to define scope and objectives and design solutions. 
• Create documentation per internal standards. 
• Work with customers to develop and write system requirements.
• Project leadership, training, and testing.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Management Information Systems, or related field, along with at least 2 years of experience
  Non-degree considered if 12+ years of related experience along with a high school diploma or GED
• Occasional travel (0-5%)
• This role is on-site 4 days per week at the New Bremen, OH location

Preferred Qualifications

• Strong experience designing, building, and supporting data solutions in Microsoft Fabric, including Lakehouses, Data Pipelines, Data Factory, Eventhouses, and OneLake.
• Proficient in developing and maintaining end-to-end data pipelines for ingestion, transformation, validation, publishing, monitoring, and operational support.
• Strong SQL expertise, including writing, optimizing, troubleshooting, and profiling queries for analytical and high-volume workloads.
• Strong Python programming skills delivering scalable, reusable, and production-grade data engineering solutions using libraries such as Pandas, PySpark, Asyncio.
• Solid understanding of data modeling principles and modern architecture patterns, including relational, dimensional, medallion, and lakehouse designs.
• Experience working with Fabric Eventhouses and KQL, including log analytics, operational monitoring, alerting, troubleshooting, and performance optimization.
• Hands-on experience monitoring and optimizing Fabric Capacity Unit (CU) consumption, workload performance, pipeline efficiency, and platform resource utilization.
• Experience integrating data from internal and external sources using Copy Jobs, Dataflows, REST APIs, and other automated ingestion frameworks.
• Proficient with Git-based source control and CI/CD practices, including GitHub and GitHub Actions, following DataOps and DevOps best practices.
• Strong focus on data quality, reliability, operational ownership, analytical problem-solving, and effective communication with technical and business stakeholders.