Rosen’s Diversified, Inc. is seeking a Senior Cloud Data Engineer to design and optimize cloud-based data solutions that support manufacturing operations, business intelligence, advanced analytics, and digital transformation. This onsite role in Green Bay, WI focuses on building secure, reliable lakehouse architectures and data pipelines that enable data-driven decisions across the organization.
You will work with Azure Databricks and related Azure services to develop scalable ETL/ELT solutions, establish reusable engineering standards, and ensure production readiness through monitoring, troubleshooting, and governed access controls.
What you’ll do
- 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 other 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, 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 monitoring, alerting, testing, and operational support practices.
- Apply organizational standards for data quality, governance, privacy, security, and compliance.
- Implement role-based access controls and governed data access using Unity Catalog and Azure security services.
- Build automated validation, auditing, and data quality controls into engineering workflows.
- Partner with business users, analysts, architects, and IT teams to translate requirements into maintainable technical solutions.
- Participate in Agile ceremonies, sprint planning, code reviews, and technical design reviews.
- Mentor junior engineers and promote best practices for coding, testing, documentation, and deployment.
Minimum qualifications
- Bachelor’s degree in computer science, information systems, data engineering, or a related field; an equivalent combination of education and experience may be considered.
- 3–5 years of experience in data engineering, cloud engineering, or analytics platform development.
- Minimum 2 years of 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 for data platforms.
- Experience with data quality, security, monitoring, troubleshooting, and performance tuning.
- Knowledge of manufacturing data domains such as 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 you’ll work with
- 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
Additional qualifications and preferences
- 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 across manufacturing and related functions.
- 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.
Rosen’s Diversified 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 for advancement.
Company context
Rosen’s Diversified, Inc. is a family-owned business established in 1946 with nearly 5,000 employees. The company has grown into a holding company of vertically integrated business units, supported by a casual, down-to-earth family culture led by innovative entrepreneurs.
As a privately held, family-owned organization across three generations, the company operates with a mentality focused on what should be done rather than shareholder requirements.
