Staff Software Engineer - (Data) - Query Optimization, Schema Design

As a Staff Software Engineer - (Data) at Tenable, your responsibilities will include designing, developing, and maintaining cloud-based search solutions, ensuring data ingestion, storage, querying, and retrieval processes are efficient and reliable. You will also collaborate closely with cross-functional teams to drive innovative solutions and enhance our cybersecurity offerings.

Tenable requires candidates for the Staff Software Engineer - (Data) position to have a B.S. degree in Computer Science or a related field, 5+ years of relevant software development experience, and a strong background in database performance tuning, schema design, and query optimization in a microservices architecture. Experience with Java or Kotlin, Kubernetes, and collaboration in Agile teams is also essential.

In the Staff Software Engineer - (Data) role at Tenable, you will work with modern cloud technologies, including microservices architectures, data management solutions, operational datastores, and frameworks like Kafka. Familiarity with languages such as Java or Kotlin will also be part of your toolkit as you build scalable, highly available systems.

At Tenable, you can expect a culture that prioritizes collaboration, respect, and continuous improvement. As part of the #OneTenable team, you'll work alongside passionate individuals dedicated to building innovative cybersecurity solutions. The company offers an environment where your contributions are valued, fostering personal and professional growth.

Tenable supports professional development by providing employees with a training budget for attending conferences and workshops. This commitment to learning ensures that as a Staff Software Engineer - (Data), you will have opportunities to expand your skill set and stay current with industry trends.

When answering this question, highlight specific projects where you successfully optimized database performance. Discuss your strategies for analyzing and improving query performance, such as indexing, reducing complex joins, and analyzing execution plans, showcasing your ability to enhance application efficiency.

In your response, emphasize your understanding of domain-driven design principles and how to create schemas that support service autonomy. Talk about collaboration with other teams to ensure data integrity across services and how you would adapt schemas over time as the applications evolve.

Discuss your experience with building pipelines that manage large volumes of data efficiently. Highlight techniques like batch versus real-time data processing and the tools or technologies you prefer for making ingestion and retrieval both efficient and robust.

Be prepared to describe the project in detail, including the business requirements, the technology stack you chose, and the architectural decisions made. Discuss your methodologies for deployment and integration with other services, as well as any challenges faced and how you overcame them.

Explain how you engage with cross-functional teams, including product managers, designers, and other engineers. Offer examples of how collaboration led to successful project outcomes and the impact it had on team dynamics and product quality.

Share a specific instance where you provided guidance to a junior developer, focusing on the skills or knowledge you imparted. Discuss the positive results of your mentorship, such as improved performance or project success, and how it contributed to their professional growth.

Mention specific tools like Helm, Kubectl, and Istio, describing how you utilize them to manage deployments and ensure the reliability and scalability of microservices. Provide examples of challenges faced and how you resolved them using these tools.

Talk about your method for assessing the business value of features versus the effort required to implement them. Emphasize the importance of stakeholder feedback and how it shapes your priorities, along with the mechanisms used for backlog grooming.

Describe your practices for testing, code reviews, and monitoring once software is in production. Discuss tools you've used for automated testing and logging, and how you react to incidents to ensure a responsive approach to quality assurance.

Share your methods for ongoing learning, such as subscribing to technical blogs, participating in online courses, and attending industry conferences. Highlight how you apply new knowledge to your projects and contribute to team discussions.