Okay, I've searched for Data Engineer Lead positions in Nashville, TN requiring 6+ years of experience, expertise in Power BI and Snowflake, and full-time onsite roles. I have found 47 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Data Engineer Lead role at NTT DATA is fundamentally designed to champion enterprise-scale business intelligence (BI) enablement through expert management of Power BI frameworks, leveraging cloud data platforms such as Snowflake, and ensuring secure, scalable, and performant data architecture. This position requires a seasoned data engineering professional who can balance deep technical expertise with a consultative, client-centric approach—resolving high-level dashboard issues, optimizing BI deployment, and automating frameworks across multiple business units. The extensive use of Power BI (with capacity management), scripting via Python and PowerShell, and hybrid cloud architectures points to a role that demands not only technical dexterity but also strategic foresight to maintain and evolve BI ecosystem health. The candidate will face challenges like ensuring seamless analytics performance across a broad enterprise, handling complex data security needs, and navigating evolving BI toolsets and cloud transitions (e.g., Microsoft Fabric). Success in this role looks like proactively preventing issues, rapidly responding to escalations, and driving continuous improvement of analytics frameworks, enabling 20+ business units with timely, secure, and insightful data visualizations. The role's multi-domain responsibilities underscore the need for prioritization and adaptability in a dynamic environment, requiring clear communication with stakeholders and deep problem-solving skills to handle ambiguities inherent in large-scale data environments.

Company Analysis:

NTT DATA stands as a global technology and business services innovator with a commanding presence, servicing a vast share of Fortune Global 100 companies. Positioned as a stable yet forward-thinking leader, NTT DATA blends traditional strength with a strong emphasis on innovation, particularly in AI, digital transformation, and infrastructure. This environment likely promotes a culture that values inclusivity, adaptability, and continuous learning—not surprising given its deep R&D investments and diverse, global talent pool. Candidates at NTT DATA can expect a balance of client-facing responsibility and collaborative teamwork, with a clear orientation toward long-term impact and sustainability. The Data Engineer Lead fits into this ecosystem as a crucial enabler of data-driven transformation, interfacing across multiple business units and technical teams, with a visible leadership footprint within the Data Village team and beyond. The strategic goal behind this hire is to scale enterprise analytics capabilities and accelerate cloud-based BI innovation—signaling this role’s potential for both technical influence and strategic contribution. The company's large size and client base necessitate professionals who can thrive in a complex, sometimes matrixed environment, who are comfortable adapting rapidly to evolving technologies and business needs while upholding rigorous standards of security and performance.

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

• Behavioral: Tell me about a time when you had to quickly troubleshoot and resolve a critical issue impacting enterprise-wide Power BI dashboards. How did you manage stakeholders and technical resolution simultaneously?
• Behavioral: Describe an experience where you led the migration or adoption of a new BI or data platform technology. What challenges did you face, and how did you overcome them?
• Behavioral: How do you prioritize multiple urgent requests across different business units, especially when managing large-scale BI frameworks under tight deadlines?
• Behavioral: Share an example of how you have coached or mentored junior team members or peers in data engineering best practices and BI tool usage.
• Technical: Walk me through your approach to designing and automating Power BI framework upgrades and instance deployments across an enterprise environment.
• Technical: How do you optimize Snowflake queries and troubleshoot connectivity issues to ensure smooth hybrid on-prem/cloud data integration?
• Technical: Explain how you would implement secure data handling and encryption protocols in an enterprise BI environment, particularly with sensitive or confidential datasets.
• Technical: What scripting strategies do you use with Python and PowerShell to build and maintain batch and streaming data pipelines for real-time analytics?
• Situational: Imagine a scenario in which multiple business units report degraded performance in Power BI dashboards after a capacity migration to Microsoft Fabric. How would you investigate and resolve this?
• Situational: Suppose a new BI requirement emerges that current frameworks don’t support well. How would you conduct a proof-of-concept to evaluate and implement this capability?
• Situational: If you discover conflicting visualization standards across business units that degrade overall reporting consistency, how would you approach standardization while maintaining stakeholder buy-in?
• Company Fit/Motivation: What excites you about the opportunity to work at NTT DATA and contribute to their Data Village team?
• Company Fit/Motivation: How do your values around innovation, adaptability, and client service align with NTT DATA’s mission and culture?
• Company Fit/Motivation: NTT DATA values sustainable digital transformation. How have you incorporated sustainability or ethical considerations into your data engineering projects?
• Candidate to Ask Interviewer: Can you describe how the Data Village team collaborates with other departments and how success is measured within this team?
• Candidate to Ask Interviewer: What are the biggest technical and organizational challenges currently facing the Power BI enterprise framework at NTT DATA?
• Candidate to Ask Interviewer: How does NTT DATA invest in professional growth and continuous learning for roles like the Data Engineer Lead?