Senior Azure SQL Database Developer

As a Senior Azure SQL Database Developer at Wellfit, your responsibilities encompass designing and implementing optimized Azure SQL database solutions, developing and maintaining complex SQL queries, and enhancing database performance. You'll also be tasked with building robust ETL pipelines using Azure Data Factory to process large datasets and ensure smooth data integration within our microservices architecture.

To qualify for the Senior Azure SQL Database Developer role at Wellfit, candidates should possess a bachelor’s degree in Computer Science or a related field, along with over 5 years of experience in Azure SQL development and 4 years in ETL processes utilizing Azure Data Factory. A strong understanding of database design principles and proven expertise in building incremental data load processes is essential.

In the Senior Azure SQL Database Developer role at Wellfit, you'll work extensively with Azure SQL Database, Azure Data Factory for ETL processes, and other related technologies. Familiarity with Azure Synapse Analytics, Data Lake, or Databricks is preferred, as well as experience with containerization tools like Docker and orchestration platforms such as Kubernetes.

As a Senior Azure SQL Database Developer at Wellfit, you can look forward to a competitive salary in the range of $125,000 to $135,000, alongside an annual bonus and benefits including a hybrid working model, unlimited paid time off, comprehensive health coverage, and a 401k matching up to 4%. We believe in supporting our team's work-life balance and overall well-being.

At Wellfit, the culture is collaborative and dynamic, perfect for a Senior Azure SQL Database Developer who thrives in an innovative environment. We encourage teamwork and creative problem-solving, providing opportunities to mentor junior team members and collaborate across departments to develop impactful, data-driven solutions in the healthcare fintech space.

When answering this question, discuss your approach to analyzing SQL query execution plans, identifying bottlenecks, and applying techniques like indexing, partitioning, and query rewriting. Provide examples of how you've utilized these strategies in past projects to achieve significant performance improvements.

Outline the steps you typically follow in an ETL process, including data extraction, transformation, and loading. Highlight your experience with Azure Data Factory and detail a specific project where you managed these components effectively, emphasizing the business outcomes of your efforts.

Discuss your understanding of microservices architecture and how it influences database design and integration. Share your experience in working with microservices, focusing on how you ensure data consistency, reliability, and performance across distributed systems.

If you have worked with Azure Synapse Analytics or Data Lake, explain your specific experience and how you leveraged these tools for data storage and analytics. Highlight a project where these technologies played a crucial role in achieving analytical insights or improving data management.

Detail the quality assurance practices you implement throughout the ETL lifecycle, such as data validation and error handling. Discuss specific examples where you’ve detected and resolved data discrepancies in previous ETL projects to maintain high data integrity.

Share your approach to task management, emphasizing the tools and methodologies you use to prioritize work, such as Agile, Kanban, or simply using a task management tool. Illustrate your strategy with examples of how you have successfully juggled multiple projects or deadlines.

Explain your mentoring philosophy and the practical steps you take to support junior data developers. Provide examples of how you’ve guided team members in gaining technical skills, sharing best practices, and fostering their professional growth within the team.

Discuss your experience with version control systems like Git and how you integrate CI/CD practices into your database development process. Explain any specific tools you’ve used and how you ensure smooth deployments and rollback processes.

Share a specific challenge related to data integration you faced and the steps you took to resolve it. Focus on the tools and techniques you employed and highlight the successful outcomes to demonstrate your problem-solving skills.

If applicable, share your experience with containerization tools like Docker in database environments. Discuss how containerization has improved your development and deployment workflow, including any specific projects where you’ve implemented it effectively.