Okay, I've searched for Data Engineer roles in Atlanta, GA, that are full-time, require skills in Python and SQL, and specify 5+ years of experience. I have found 152 positions matching your criteria.

Sure. Here's the analysis:

Job Analysis:

This Data Engineer role is fundamentally about enabling the organization’s data-driven decision-making by architecting and maintaining a robust Enterprise Data Warehouse and ETL ecosystem. Beyond just building data pipelines, the candidate is expected to collaborate closely with business stakeholders to translate their analytical needs into efficient data solutions, which requires both technical depth and business acumen. Given the tech stack—Snowflake, Azure Data Factory, SSIS, SQL Server, Python, and C#—the role demands solid expertise in cloud-based data warehousing, pipeline orchestration, and performance optimization, reflecting a need to handle large and complex datasets efficiently. The extensive experience requirements signal that this role is for someone seasoned who can work independently to identify bottlenecks, innovate ETL processes, and introduce improvements leveraging both traditional and emerging technologies such as Machine Learning and Master Data Management. Success in this role means enabling a seamless, scalable data platform that drives business intelligence and analytics, providing timely, accurate, and optimized data access for end users. The hybrid work setting calls for a candidate who is self-motivated but also thrives in collaborative environments, able to communicate effectively across technical teams and non-technical stakeholders. They will frequently make decisions involving trade-offs between performance, maintainability, and scalability, requiring good judgment and experience navigating ambiguity in fast-evolving data landscapes.

Company Analysis:

Tier4 Group operates in the talent and professional services technology sector, with a strong emphasis on diversity and inclusion as a women-owned and diversity-certified firm. Their positioning as a national player specializing in IT consulting, advisory, and cybersecurity means they value flexibility, customer-centric solutions, and high service quality. For a Data Engineer, this environment likely means working on client-facing projects or internal initiatives where agility, adaptability, and cross-functional collaboration are essential. The culture appears mission-driven and inclusive, focused on leveraging diverse expertise to deliver tailored technology solutions rather than a rigid, hierarchical structure. This bodes well for candidates who enjoy working in supportive teams that value their contributions and encourage ongoing learning. Given the company’s advisory and cybersecurity orientation, the role may intersect with security-driven data governance or compliance elements, adding a strategic layer to the technical responsibilities. The position fits into a broader team of experts, likely reporting into technical leadership with some visibility into business strategy. This role not only supports Tier4’s internal data capabilities but also positions the engineer as a critical enabler of modern data ecosystems that help Tier4 maintain its competitive edge and client satisfaction, making it a strategic hire focused on innovation and operational excellence.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to optimize a complex ETL process under tight deadlines. How did you approach it and what was the outcome?
• Behavioral: Describe an instance where you collaborated with non-technical stakeholders to design a data solution. How did you ensure their needs were met?
• Behavioral: Can you share an experience where you identified and resolved a significant performance bottleneck in a data warehouse environment?
• Behavioral: Talk about a situation where you had to stay current with emerging data technologies and apply them practically. How did this impact your project?
• Technical: How would you design and implement an ETL pipeline using Azure Data Factory and Snowflake to handle both structured and unstructured data?
• Technical: Explain your experience with Master Data Management (MDM) and how you integrated MDM practices into a data engineering workflow.
• Technical: Given a slow-running SQL query in a large data warehouse, what steps would you take to troubleshoot and optimize its performance?
• Technical: Discuss how you have used Python and C# together in developing data pipelines or automation workflows.
• Situational: Imagine a critical data feed stops working just before a major business intelligence reporting deadline. How would you handle the situation?
• Situational: You receive conflicting requirements from two different business units regarding data access and structure. How do you resolve this?
• Situational: Suppose you identify a new technology that could significantly improve ETL efficiency but requires team-wide adoption. How would you advocate for this change?
• Company Fit: Why are you interested in joining Tier4 Group, especially given its focus on diversity and technology consulting?
• Company Fit: How do your professional values align with working in a women-owned and diversity-certified company focused on client service and innovation?
• Company Fit: What excites you most about contributing to a national, flexible technology services firm with a hybrid work environment?
• Questions for Interviewer: Can you describe the current data engineering team structure and how this role collaborates with other IT and business units?
• Questions for Interviewer: How does Tier4 Group support continuous learning and professional growth in emerging data technologies for its engineering staff?
• Questions for Interviewer: What are the company's priorities for the data platform over the next 12 months, and how would this role impact those goals?