Senior Cloud Data Engineer

Build and optimize secure, high-performing cloud data solutions on Azure for manufacturing analytics and digital transformation.

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks, PySpark, Python, and SQL
• Build and optimize ingestion frameworks for ERP, MES, Industrial IoT, quality, supply chain, inventory, finance, and related operational systems
• Create reusable engineering patterns and standards to improve delivery speed, supportability, and reliability
• Implement lakehouse solutions using Delta Lake and Medallion Architecture across Bronze, Silver, and Gold layers
• Design and optimize data models for reporting, analytics, AI, and machine learning use cases
• Maintain data lineage and documentation, including metadata, technical documentation, and operational runbooks
• Integrate Azure Databricks with Azure Data Factory, Azure Data Lake Storage Gen2, Azure Key Vault, Microsoft Fabric, Power BI, and Azure DevOps
• Support orchestration and data movement between enterprise applications and cloud platforms
• Monitor and optimize Databricks clusters, jobs, notebooks, and workflows for performance, scalability, and cost efficiency
• Troubleshoot production issues, identify root causes, and implement sustainable corrective actions
• Contribute to operations, including monitoring, alerting, testing, and operational support practices
• Apply standards for data quality, governance, privacy, security, and compliance
• Implement governed data access with role-based access controls using Unity Catalog and Azure security services
• Build automated controls for validation, auditing, and data quality within engineering workflows
• Collaborate with stakeholders including business users, analysts, architects, and IT teams to translate requirements into maintainable solutions
• Participate in Agile delivery with sprint planning, code reviews, and technical design reviews
• Mentor junior engineers and promote best practices for coding, testing, documentation, and deployment

Requirements

• Bachelor’s degree in computer science, information systems, data engineering, or related field; equivalent education and experience may be considered
• 3–5 years of experience in data engineering, cloud engineering, or analytics platform development
• Minimum 2 years hands-on experience developing solutions with Azure Databricks
• Experience supporting enterprise data solutions in a manufacturing or industrial environment
• Strong knowledge of Azure Databricks, Apache Spark, PySpark, Python, SQL, Delta Lake, lakehouse architecture, data modeling, and data warehousing concepts
• Experience with Azure Data Lake Storage Gen2, Azure Data Factory, Azure DevOps, Git source control, and CI/CD practices
• Experience with data quality, security, monitoring, troubleshooting, and performance tuning
• Knowledge of manufacturing data domains including ERP, MES, production planning, inventory, supply chain, quality management, maintenance, or Industrial IoT
• Ability to work with operational stakeholders and translate manufacturing processes into reliable data requirements and solutions

Technologies

• Azure Databricks
• PySpark, Python, SQL
• Delta Lake, Medallion Architecture
• Azure Data Factory
• Azure Data Lake Storage Gen2
• Azure Key Vault
• Microsoft Fabric
• Power BI
• Azure DevOps
• Unity Catalog
• Terraform, Bicep, ARM templates
• Git, CI/CD

Benefits

• Excellent health and welfare benefits including medical, dental, vision, disability, and voluntary benefit options
• 401(k) with annual company match for eligible employees
• Professional and personal development programs, including Career and Learning Paths

Additional qualifications, knowledge, skills, and experience

• Experience with Microsoft Fabric, Power BI, or real-time and streaming data workloads
• Hands-on experience with Unity Catalog and governed lakehouse implementations
• Exposure to machine learning or AI data preparation and deployment patterns
• Experience with Infrastructure as Code using Terraform, Bicep, or ARM templates
• Preferred knowledge of Infor M3, including application design, business data model, and core table structures used across manufacturing, supply chain, inventory, finance, and related functional areas
• Preferred understanding of production, planning, inventory, quality, maintenance, and supply chain processes
• Microsoft Certified: Azure Data Engineer Associate
• Databricks Certified Data Engineer Associate or Professional
• Microsoft Certified: Fabric Analytics Engineer Associate

Location: Green Bay, WI (onsite). Minimum experience: 3 years. Education: Bachelor’s degree in computer science, information systems, data engineering, or a related field.