Data Analytics Engineer

Job Role

The Senior Data Analytics Engineer serves as a key technical and analytical partner within Kirkhill, developing and optimizing systems, data, analytics, and automation. This position supports all of Kirkhill, with an emphasis on Production, Supply Chain, and Quality.

Working cross-functionally across the organization, this role translates complex manufacturing and business requirements into practical technical solutions. The position combines manufacturing and ERP expertise with strong capabilities in SQL Server, Power BI, Python, Excel, Microsoft Power Platform, and emerging AI technologies.

Responsibilities

Manufacturing Systems & Analytics

Partner with Operations and other stakeholders to understand manufacturing processes, identify system and data gaps, and develop solutions that improve factory performance. Design reporting, dashboards, and analytical tools that provide actionable visibility into production, capacity, WIP, material availability, quality, backlog, and on-time delivery.

ERP, Planning & Decision Support

Develop analytical and automation solutions around Infor CSI/Syteline ERP, including production planning, APS/MRP, scheduling, jobs, BOMs, routings, inventory, purchasing, and material transactions. Develop data-driven scheduling and decision-support solutions that improve production priorities, material visibility, capacity planning, and projected completion dates.

Data Engineering, Integration & Automation

Design and maintain SQL Server data models, queries, stored procedures, ETL processes, and other data solutions supporting factory analytics and operational applications. Integrate and automate business processes using SQL, Python, REST APIs, Power Automate, Power Apps, Excel/VBA, and related technologies.

Artificial Intelligence & Advanced Analytics

Identify and implement practical applications of AI and advanced analytics within manufacturing and business operations, including document intelligence, large language models, intelligent workflow automation, anomaly detection, and predictive analytics. Evaluate solutions based on measurable business value, accuracy, security, maintainability, and data quality.

Continuous Improvement & Solution Ownership

Use operational data to identify bottlenecks, production risks, data-quality issues, and opportunities for process improvement. Own solutions from requirements and technical design through development, testing, deployment, documentation, training, and ongoing support.

Technical Leadership & Strategy

Contribute to the long-term factory information systems strategy, including integration of ERP, manufacturing, quality, BI, automation, and AI technologies. Provide technical leadership, mentorship, standards, and best practices for analysts, engineers, and business users.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related technical discipline.
• 6+ years of experience in manufacturing systems, business intelligence, data analytics, business systems analysis, or a related technical role.
• Advanced proficiency with Microsoft SQL Server and T-SQL, including complex query development and optimization.
• Strong experience with Power BI, data modeling, DAX, Power Query, Excel, and operational reporting.
• Experience developing data-processing, integration, and automation solutions using Python, APIs, Microsoft Power Platform, or similar technologies.
• Experience with ERP/MRP systems and manufacturing data, including production planning, BOMs, routings, inventory, materials, and scheduling.
• Strong understanding of manufacturing operations and concepts such as WIP, capacity, throughput, material availability, lead time, and on-time delivery.
• Demonstrated ability to independently analyze complex operational problems, develop practical technical solutions, and communicate effectively with technical and non-technical stakeholders.

Preferred Qualifications

• Strong experience with Infor CSI/Syteline, including its SQL data model and APS/MRP functionality.
• Experience developing factory scheduling, capacity planning, WIP, material-planning, and production-performance solutions.
• Experience integrating ERP, MES, quality, planning, or other manufacturing systems.
• Practical experience implementing AI-enabled business or manufacturing solutions, predictive analytics, or intelligent workflow automation.