Senior Cloud Data Engineer

The ideal candidate combines hands-on cloud data engineering experience with collaboration across business stakeholders, analysts, architects, and data engineers to deliver reliable, secure, and high-performing data products that enable data-driven decisions across the organization. The Senior Cloud Data Engineer designs, develops, and optimizes scalable data solutions that support manufacturing operations, business intelligence, advanced analytics, and digital transformation.

Overview
JOB SUMMARY

The Senior Cloud Data Engineer designs, develops, and optimizes scalable data solutions that support manufacturing operations, business intelligence, advanced analytics, and digital transformation. This role builds and maintains cloud-based data pipelines using Azure Databricks and related Azure services to integrate enterprise operational and business data. The ideal candidate combines hands-on cloud data engineering experience with collaboration across business stakeholders, analysts, architects, and data engineers to deliver reliable, secure, and high-performing data products that enable data-driven decisions across the organization .

Essential Functions and Responsibilities

• 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.
• Develop reusable engineering patterns and standards that improve delivery speed, supportability, and reliability.
• Implement and support 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 movement of data 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 coding, testing, documentation, and deployment best practices.

Qualifications
QUALIFICATIONS, KNOWLEDGE, SKILLS, AND EXPERIENCE

• 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.

ADDITIONAL SKILLS/EXPERIENCE/REQUIREMENTS

• 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 its 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