Analytics Engineer

MDI Group

MDI Group is looking for an Analytics Engineer to streamline data processes at Alex Lee. This position focuses on optimizing Azure-based data pipelines and models, facilitating effective business intelligence and reporting. The role aligns at the crossroads of data engineering and analytics, particularly within the grocery and retail sectors, requiring collaboration across multiple teams to support enterprise-wide data initiatives.

In this role you can expect to have the responsibilities:

• Develop and manage ETL/ELT data pipelines using the Microsoft Azure ecosystem, including SSIS, Azure Data Factory, and Azure Synapse Analytics.
• Implement workflows utilizing SQL, Python, and Azure Data Factory for data integration.
• Incorporate data from retail, independent grocery retailers, and external sources like loyalty programs.
• Create scalable data models to support retail operations, sales trends, and customer insights.
• Structure data models within Azure Synapse Analytics and Microsoft SQL Server for clarity and ease of use.
• Coordinate with business units to align data models with analytical needs and Power BI dashboards.
• Ensure accuracy through data validation and transformation processes.
• Collaborate on data governance to maintain security and compliance standards.
• Perform root cause analysis to resolve data issues in retail analytics.

This role requires you to have:

• Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or related field.
• 5+ years of experience in data analytics, data engineering, or software engineering.
• Proficiency in SQL development, data modeling, and ETL pipeline development with Microsoft tools.
• Experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft SQL Server.
• Strong skills in SQL, Python, and T-SQL for data processing.
• Expertise in Azure data tools and Power BI for DAX calculations.

You would benefit from having:

• Familiarity with Azure DevOps for CI/CD in data engineering.
• Experience in data governance practices.
• Strong analytical and problem-solving abilities.
• Collaboration skills across IT, business, and analytics teams.
• Excellent communication skills.