As an Analytics Engineer at Alex Lee, you will play a critical role in ensuring that data is ingested, transformed, and readily available for analytical and reporting purposes. You will be responsible for building and optimizing Azure-based data pipelines, creating data models within the Microsoft ecosystem, and ensuring data quality and governance to empower business intelligence and decision-making.
This role sits at the intersection of data engineering and analytics, requiring expertise in Microsoft technologies and an understanding of retail-owned and independent grocery data. You will work with point-of-sale (POS) transactions, supply chain data, customer behavior analytics, and third-party vendor integrations, ensuring insights are accessible across both corporate and independent grocery operations.
The Analytics Engineer will report directly to the Manager of Data Engineering, collaborating closely with cross-functional teams to support enterprise data initiatives.

• Design, develop, and maintain ETL/ELT data pipelines within the Microsoft Azure ecosystem (SSIS, Azure Data Factory, Azure Synapse Analytics, Azure Databricks).
• Implement data workflows using SQL, Python, and Azure Data Factory to integrate structured and unstructured data sources.
• Integrate data from retail-owned stores, independent grocery retailers, and third-party sources such as loyalty programs and promotions.
• Develop and maintain scalable, reusable data models to support analytics for retail operations, sales trends, inventory management, and customer insights.
• Design and optimize data models within Azure Synapse Analytics and Microsoft SQL Server to provide clean, structured datasets for data analysts and business teams.
• Ensure data models align with business needs and are structured for efficient querying, aggregation, and integration with Power BI dashboards (built by analysts).
• Collaborate with business teams to understand their analytical requirements, translating them into optimized data structures that facilitate reporting and insights.
• Implement data validation and transformation logic to ensure data models are accurate, reliable, and consistent across retail-owned and independent grocery datasets.
• Implement data validation, monitoring, and error-handling processes to ensure data integrity and accuracy.
• Collaborate with data governance teams to enforce security, compliance, and data-sharing policies.
• Conduct root cause analysis on data issues, ensuring accurate reporting for retail-owned and independent grocery analytics.

• Bachelor’s in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related field.
• 5+ years of experience in data analytics, data engineering, or software engineering roles.
• Expertise in SQL development, data modeling, and ETL pipeline creation within the Microsoft ecosystem.
• Experience working with Azure Data Factory, Azure Synapse Analytics, and Microsoft SQL Server.
• Experience working with grocery or retail data (e.g., POS systems, loyalty programs, supply chain, and merchandising analytics).
• Strong proficiency in SQL, Python, and T-SQL for data processing.
• Expertise in Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Microsoft SSIS, and Microsoft SQL Server.
• Hands-on experience with data modeling best practices, indexing, partitioning, and query performance optimization in Azure.
• Proficiency in Power BI, including developing and optimizing DAX calculations for efficient data modeling and compute back-end performance.
• Familiarity with Azure DevOps for CI/CD in data engineering workflows.
• Experience with data governance best practices.
• Strong analytical thinking and problem-solving ability.
• Ability to work collaboratively across IT, business, and analytics teams.
• Excellent communication skills, with the ability to translate business needs into technical solutions.
• Results-driven mindset, ensuring that data models, ETL processes, and engineering solutions deliver measurable business impact.