Manager, Data Engineering 

The Data Engineering Manager at Interwell Health is responsible for spearheading the development and optimization of data pipelines and workflows. This pivotal role includes overseeing the design, implementation, and optimization of data architecture, leading a team of engineers, and ensuring robust data quality and monitoring systems. You'll also manage projects, ensuring timely delivery and compliance with data governance frameworks.

Candidates for the Data Engineering Manager role at Interwell Health should have 3-5 years of related experience in data engineering, a bachelor's degree (or a master's degree with lesser experience), and a strong understanding of data lake architecture and data warehousing concepts. Expertise in Azure Data Factory pipelines, Databricks, and cloud migration is crucial. Moreover, strong communication and presentation skills are essential for this leadership position.

The Data Engineering Manager at Interwell Health should be adept in technologies such as Azure MI, Databricks, Azure Data Factory, and OneLake. Familiarity with MS SQL stack, including SSIS and ADF, as well as Python for data processing, is also required to effectively lead the engineering team and optimize data solutions.

At Interwell Health, the team environment for the Data Engineering Manager is collaborative and supportive. You'll work closely with data engineers, data scientists, and various stakeholders to drive projects and optimize data solutions. The emphasis on teamwork aligns with our mission-driven values, fostering a culture where everyone’s contributions are valued and help shape the organization’s success.

Interwell Health is committed to diversity, equity, and inclusion throughout our hiring practices for the Data Engineering Manager role. We encourage applications from candidates of all backgrounds, recognizing that diverse experiences enhance our team. We appreciate different journeys and perspectives, and we invite anyone who is enthusiastic about our mission to apply, even if not meeting every requirement.

In answering this question, focus on your past experiences in optimizing data pipelines. Discuss specific tools and practices you've implemented to ensure data integrity, accuracy, and timely processing, emphasizing any relevant projects from your previous roles.

Share specific examples of how you've led and mentored teams. Highlight your strategies for fostering collaboration, setting clear goals, and ensuring that your team members have opportunities for professional development, reflecting on how these contribute to successful project outcomes.

Discuss the techniques and tools you've used to ensure data quality, including specific monitoring systems you've set up. Emphasize the importance of proactive monitoring and how you enforce data quality standards within your team to prevent issues.

In your response, outline the project management methodologies you prefer, such as Agile or Scrum. Provide examples of how these strategies have helped you deliver projects on time and within scope while managing risks and resources effectively.

Outline a specific example where you designed a complex data architecture. Describe the challenges faced, tools used, and the ultimate impact of the architecture on the organization’s data strategy and decision-making, showcasing your problem-solving skills.

Discuss your hands-on experience with Azure services, specifically highlighting projects that involved Azure Data Factory and Databricks. Detail your role in these projects and how you leveraged these technologies to improve data processing and analytics.

Detail your understanding of data governance and provide examples of frameworks you've implemented in your previous roles. Emphasize your commitment to data lineage, auditing, and compliance standards to ensure organizational accountability.

Share your approach to continuous learning, such as attending industry conferences, participating in online courses, or following thought leaders in the data engineering space. Highlight the importance of keeping your skills and knowledge current to benefit your team and organization.

Describe specific initiatives or practices you've employed to promote diversity and inclusion within your team. Discuss how you value diverse perspectives, ensure equitable opportunities, and create an environment where all team members feel included.

Reflect on your personal motivations for working in data engineering and how you align them with Interwell Health's mission. Share stories about how data-driven insights can impact patient care and outcomes, and how that motivates your work.