Okay, I've searched for Lead Azure Data Engineer roles in Atlanta, GA, full-time, requiring 10+ years of experience, with skills in Data Vault modeling and Azure Cloud services. I have found 47 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Lead Azure Data Engineer role is fundamentally about architecting, leading, and executing enterprise-scale data engineering solutions on the Azure cloud platform, focusing heavily on modern data warehousing techniques, particularly Data Vault 2.0 modeling. The candidate will be expected to design and optimize scalable ETL/ELT pipelines, ensuring efficient data flow management across diverse sources using tools native to Azure such as Data Factory, Synapse Analytics, and Databricks. This role requires bridging business needs with technical execution, collaborating closely with data architects, analysts, and stakeholders to transform complex data requirements into actionable and maintainable data solutions. The emphasis on Microsoft Fabric and emergent technologies signals a forward-looking, adaptable approach, meaning the successful candidate must balance deep technical expertise with a willingness and vision to lead technological innovation. Mentorship and leadership responsibilities further underscore the need for strong communication skills and the ability to cultivate team growth. Problem-solving will be multi-dimensional—from troubleshooting pipeline inefficiencies to navigating evolving data governance standards. Success in this role looks like robust, secure, and scalable data architecture that meets business analytics demands while pioneering Azure-based best practices and supporting the team to elevate overall data engineering maturity.

Company Analysis:

Dice serves as a prominent career platform specialized in tech roles, functioning both as a conduit and a community for technology professionals across various career stages. While the specific client—Parkar Consulting Group, LLC—is the direct employer, Dice's ecosystem reflects a culture that values continuous learning, career growth, and tech-driven innovation. This environment suggests that while the role is a contract position, the expectation is to be part of a fast-evolving, knowledge-rich setting where staying abreast of industry trends and adopting new skills rapidly is crucial. The lack of traditional benefits indicates a contractor context, emphasizing autonomy and self-motivation. The hybrid setup in Atlanta also speaks to a modern flexibility balanced with team collaboration needs. Strategically, this hire appears aimed at scaling and leading Azure data engineering capabilities within Parkar's engagements, aligning with broader client demands for advanced cloud data solutions. The role's visibility likely includes significant interaction with technical leadership and multiple stakeholder groups, positioning the lead engineer as both a technical linchpin and a strategic influencer in data architecture decisions.

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

• Behavioral: Tell me about a time when you led a data engineering project using Azure cloud services. What challenges did you face and how did you overcome them?
• Behavioral: Describe an instance where you had to mentor a junior data engineer or lead a team through a complex technical problem. What approach did you take?
• Behavioral: Share a situation where you collaborated with business stakeholders to translate ambiguous data requirements into a concrete technical solution. How did you ensure alignment?
• Behavioral: How have you adapted to emerging data engineering technologies or methodologies in past roles? Can you give an example?
• Technical: Can you walk me through your experience designing and implementing Data Vault 2.0 models? What are the key benefits of using this methodology?
• Technical: How do you approach building scalable and maintainable ETL/ELT pipelines on Azure Data Factory and Synapse Analytics?
• Technical: What are the nuanced differences and potential advantages of using Databricks with Apache Spark for data transformation in an Azure environment?
• Technical: Describe your experience or strategy for integrating Microsoft Fabric into a data engineering stack. How do you evaluate and lead adoption of new tools?
• Situational: Imagine your team encounters significant data quality issues just before a critical business reporting deadline. How would you manage the situation?
• Situational: You notice that the current cloud data architecture is struggling to cope with growing data volumes and query complexity. How would you address this problem?
• Situational: Suppose a stakeholder requests a data solution that conflicts with best practices for data governance and security. How would you handle the conversation and outcome?
• Company Fit/Motivation: What attracts you to working with Parkar Consulting Group and the Dice platform, specifically in a contract capacity?
• Company Fit/Motivation: How do your professional values and career goals align with Dice's mission of supporting continuous learning and tech career advancement?
• Company Fit/Motivation: Given the pace of change in cloud data engineering, how do you stay current and motivated to continually upskill in this field?
• Candidate Questions: Can you describe the current team structure and how the Lead Azure Data Engineer interfaces with other business and technical units?
• Candidate Questions: What are the critical success factors for this role in the first 6 to 12 months, and how will performance be measured?
• Candidate Questions: How open is the organization to adopting emerging technologies like Microsoft Fabric, and what level of autonomy does this role have in influencing such decisions?