Analytics Engineer

As an Analytics Engineer at Alex Lee, you will design, develop, and maintain ETL/ELT data pipelines within the Microsoft Azure ecosystem, implement data workflows using SQL and Python, and develop scalable data models for retail operations. Your role will also include collaborating with business teams to understand their analytical requirements and ensuring data quality and governance.

To apply for the Analytics Engineer role at Alex Lee, candidates should have a Bachelor's degree in Computer Science, Data Science, or a related field, along with 5+ years of experience in data analytics or engineering. Strong skills in SQL, Azure Data Factory, and data modeling are essential, especially with retail data experience being highly beneficial.

In the role of Analytics Engineer at Alex Lee, you will collaborate with data governance teams to enforce security and compliance policies, implement data validation processes, and conduct root cause analyses on data issues to ensure integrity across retail datasets. Your contributions are key to ensuring that data used for analytics is reliable and accurate.

Candidates for the Analytics Engineer role at Alex Lee need proficiency in SQL, Python, and T-SQL, as well as hands-on experience with Azure Data Factory, Azure Synapse Analytics, and Microsoft SQL Server. Familiarity with Power BI for developing business insights and Azure DevOps for CI/CD processes is also important.

The work environment for an Analytics Engineer at Alex Lee is collaborative and dynamic, where you will work closely with IT, business units, and analytics teams. You'll have the opportunity to share insights and solutions, making an impactful difference in how data supports both corporate and independent grocery operations.

When answering this question, be specific about your experience with ETL/ELT pipeline development in Azure Data Factory or other Azure tools. Mention any projects you've worked on, the challenges faced, and how your solutions improved data handling and reporting efficiency.

Discuss your approach to data modeling, focusing on best practices such as normalization, indexing strategies, and how you ensure data integrity. Highlight any projects that required complex data models and the outcomes from your modeling techniques.

Talk about the processes you implement for data validation, error-handling, and monitoring. Give examples of how you've collaborated with governance teams and adhered to compliance regulations in previous roles.

Detail your hands-on experience with these platforms, mentioning specific projects where you utilized them. Emphasize your skills in creating data pipelines and performing data transformations, highlighting positive results or efficiencies gained in your previous roles.

Explain your approach to integrating data from various sources, ensuring data consistency, and addressing compatibility challenges. Discuss any tools or strategies you've used for merging and cleaning data effectively.

Discuss your understanding of indexing, partitioning, and regular performance tuning. Provide examples of how you've optimized queries in the past and the impact it had on data retrieval times or overall application performance.

Provide a specific example where you successfully collaborated with business teams to develop insights from data sets. Focus on how you extracted valuable information that impacted business decisions and your process of ensuring clarity in communication.

Outline your experience with Power BI, highlighting specific dashboards or reports you've created. Discuss your understanding of DAX calculations and how they enhance analytical capabilities within Power BI.

Discuss your proactive approach to learning, such as attending webinars, reading industry blogs, or participating in online courses. Highlight any recent advancements in data analytics that you've implemented or explored.

Elaborate on the methodologies you follow when approaching analytics issues, like root cause analysis or hypothesis testing. Provide examples of challenges you've successfully navigated and how your approach resulted in effective solutions.