Data Engineer (Microsoft stack)

at  Stem Search Group

What you’ll do…

• Data Architecture Design: Develop and maintain a scalable, efficient, and secure data architecture utilizing Azure services, SQL Server, Dynamics 365, and Power Platform.
• Data Modeling: Create and maintain conceptual, logical, and physical data models, ensuring they align with the overall data strategy and business requirements.
• Integration Solutions: Design and implement data integration solutions, leveraging Azure Data Factory, Logic Apps, and Power Automate to ensure seamless data flow across systems.
• Database Management: Provide recommendations for database design, performance tuning, and optimization for SQL Server and Azure SQL Database environments.
• Data Governance: Establish and enforce data governance policies to ensure data quality, consistency, and security across all data systems.
• Collaboration: Work closely with cross-functional teams to understand data requirements and deliver effective solutions.
• Documentation: Create comprehensive documentation for data architecture, including design specifications, data dictionaries, and operational procedures.
• Innovation: Stay current with industry trends and best practices in data architecture and recommend improvements to enhance data management capabilities.

• Data Architecture Design: Develop and maintain a scalable, efficient, and secure data architecture utilizing Azure services, SQL Server, Dynamics 365, and Power Platform.
• Data Modeling: Create and maintain conceptual, logical, and physical data models, ensuring they align with the overall data strategy and business requirements.
• Integration Solutions: Design and implement data integration solutions, leveraging Azure Data Factory, Logic Apps, and Power Automate to ensure seamless data flow across systems.
• Database Management: Provide recommendations for database design, performance tuning, and optimization for SQL Server and Azure SQL Database environments.
• Data Governance: Establish and enforce data governance policies to ensure data quality, consistency, and security across all data systems.
• Collaboration: Work closely with cross-functional teams to understand data requirements and deliver effective solutions.
• Documentation: Create comprehensive documentation for data architecture, including design specifications, data dictionaries, and operational procedures.
• Innovation: Stay current with industry trends and best practices in data architecture and recommend improvements to enhance data management capabilities