Okay, I've searched for Senior Data Architect roles that are remote, in the technology industry, requiring 8+ years of experience, and proficiency with Azure and Snowflake. I have found several positions matching your criteria. Would you like me to show the top listings now?

Sure. Here's the analysis:

Job Analysis:

The Senior Data Architect at Envista serves a pivotal role in evolving the company's enterprise data and analytics infrastructure, primarily driving the migration from on-premises data systems to a modern cloud-based environment using Azure and Snowflake. Beyond just coding or system design, this role demands a strategic architect who can bridge technical capabilities with business needs, translating complex functional requirements into scalable, efficient, and high-quality data products and pipelines. It requires hands-on expertise with building data solutions, mentoring junior engineers, and a deep understanding of data modeling methodologies such as Kimball or Inmon. The role is inherently cross-functional, involving close collaboration with analysts, source system owners, and business stakeholders to ensure that data solutions not only meet immediate reporting and analytics needs but are also future-proofed for growth, incorporating automation, data governance, and data quality improvements. Success in this job is not just measured by the technical delivery of migrating systems but by the ability to create a self-service data environment accessible to thousands of users globally and by fostering continuous improvements within the team and technology stack. Candidates should expect to navigate ambiguous requirements, deal with legacy system constraints during migration, and influence stakeholders to adopt new workflows and tools, positioning themselves as both technical leaders and trusted partners to business units.

Company Analysis:

Envista operates as a prominent global player in the dental products industry with a clear mission to improve lives by empowering dental professionals through innovative products and technology. Since its spin-off in 2019, Envista combines a culture rooted in continuous improvement with strong customer-focus and innovation, hallmarks of the Envista Business System (EBS). This creates an environment that values practical results, operational excellence, and technology-driven transformation. Given that the data architect position supports a globally distributed user base across 30 sites, the culture likely demands flexibility, collaboration, and an adaptive mindset, especially as the company shifts to modern data architectures to sustain growth and innovation in dental healthcare technologies. The role is situated within an enterprise data and analytics team, suggesting a collaborative setting with regular interaction across IT, business analytics, and operational teams, offering the opportunity for high visibility and influence. From a strategic perspective, this hire is clearly a growth-focused, transformational role, essential for achieving Envista’s ambition to leverage data as a competitive advantage—improving decision-making, operational efficiency, and innovation capabilities. For the right candidate, Envista promises a dynamic, mission-driven workplace with a commitment to diversity and equity, where technical excellence meets meaningful impact on healthcare professionals and their patients globally.

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

• Behavioral: Tell me about a time when you had to lead a data migration project involving multiple legacy systems. What challenges did you face and how did you overcome them?
• Behavioral: Describe an instance where you had to translate complex business requirements into a technical data solution. How did you ensure alignment and stakeholder satisfaction?
• Behavioral: Can you share an experience where you mentored a junior team member or helped improve team practices related to data architecture?
• Behavioral: Explain a situation where you identified a data quality issue in an existing pipeline. What steps did you take to address it and prevent future occurrences?
• Technical: Walk me through your experience architecting data solutions in Azure and Snowflake. How do you optimize performance and cost-effectiveness in these environments?
• Technical: How do you approach designing and implementing scalable data pipelines using Azure Data Factory or similar tools?
• Technical: Can you explain your experience with data modeling methodologies such as Kimball or Inmon and how you applied them in real-world projects?
• Technical: What strategies do you use for automating deployments and ensuring CI/CD in data pipeline environments?
• Situational: Imagine a key data source system you rely on unexpectedly changes its format mid-migration. How would you handle this disruption to keep the project on track?
• Situational: You're tasked with improving data lineage and governance for hundreds of datasets. What steps and tools would you prioritize to create a reliable self-service data catalog?
• Situational: Suppose you find that business stakeholders are resistant to adopting the new cloud data platform you've architected. How do you facilitate adoption and demonstrate its value?
• Company Fit: Why are you interested in working for Envista and contributing to its data and analytics transformation in the dental industry?
• Company Fit: Envista emphasizes continuous improvement and customer focus. How do your professional values and working style align with this culture?
• Company Fit: Given Envista's global footprint and multiple product lines, how would you manage prioritization when data requests compete across different business units?
• Questions for Interviewer: How does Envista envision the evolution of its data and analytics capabilities over the next 3 to 5 years?
• Questions for Interviewer: Can you describe the current team dynamics within the Enterprise Data & Analytics group and how this role interacts with business stakeholders?
• Questions for Interviewer: What are the biggest technical or organizational challenges the team faces during the cloud data architecture migration?