Principal Data Platform Engineer

As a Principal Data Platform Engineer at VivaCity, you will take charge of designing, enhancing, and managing large-scale data systems. You'll focus on ensuring the reliability, simplicity, and cost-effectiveness of our infrastructure, leveraging technologies such as Apache Kafka, Kubernetes, and PostgreSQL. Your role will require you to mentor colleagues, establish technical standards, and lead architectural decision-making, ensuring that our data platforms efficiently support our vision of smarter, more sustainable cities.

To qualify for the Principal Data Platform Engineer role at VivaCity, you'll need a strong background in distributed systems and cloud infrastructure, especially with tools like Apache Kafka, Kubernetes, and PostgreSQL. Experience in Unix systems, particularly Linux, is crucial. Additionally, excellent communication skills are necessary as you will be mentoring engineers and collaborating with different teams. A passion for solving challenges and a desire to learn will set you apart in this dynamic environment.

At VivaCity, we believe in fostering a culture of continuous learning and growth. As a Principal Data Platform Engineer, you will have plenty of opportunities to mentor junior engineers and share your expertise. We also encourage participation in technical leadership initiatives, allowing you to help establish engineering standards and user documentation. The collaborative nature of our work environment means you'll learn from peers and contribute to innovative projects that propel your career forward.

In the Principal Data Platform Engineer role at VivaCity, you'll work primarily with Apache Kafka, Kubernetes, PostgreSQL, and various cloud services on Google Cloud Platform. Additionally, familiarity with DevOps tools, Infrastructure as Code (like Terraform), and experience with programming in Go or TypeScript will be beneficial as you navigate and optimize our tech stack.

A typical day for a Principal Data Platform Engineer at VivaCity involves a blend of proactive and reactive technical work. You’ll spend time improving system reliability and optimizing performance while also responding to incidents and assisting engineers with code reviews. Additionally, you'll engage in technical leadership by helping set standards and conducting training sessions, all within a flexible working environment that supports creativity and collaboration.

When discussing your experience with Apache Kafka, focus on specific projects where you managed Kafka brokers, handled scaling, and performed upgrades. Highlight how you've integrated Kafka with high-throughput data pipelines and any challenges you faced during implementation. Show your understanding of Kafka's role in real-time data processing and why it's critical for data-intensive applications.

In your response, detail the steps you take when designing a cloud data pipeline. Discuss your prioritization of reliability and cost-effectiveness, the tools you leverage (like Kubernetes), and how you ensure smooth data flow while addressing potential bottlenecks. Use examples to illustrate how your designs have benefited previous projects.

When answering this question, share your methodology for incident management, including monitoring, logging, and evaluating incidents. Discuss how you communicate issues across teams and your strategies for minimizing downtime. Use specific examples to highlight successful resolution of incidents you’ve managed in the past.

Discuss your commitment to continuous improvement by giving examples of how you've iteratively optimized systems. Mention how you incorporate feedback, monitor performance metrics, and assess the operational costs over time. This will demonstrate your proactive approach to enhancing system functionality.

When discussing mentorship, share specific instances where you have successfully helped engineers grow in their roles. Talk about how you’ve established a collaborative environment, the techniques you use for imparting knowledge, and the importance of encouraging questions and discussions within your team.

When addressing documentation, emphasize its importance in promoting knowledge sharing and supporting scalability within teams. Discuss your experience in creating and maintaining documentation for technical processes, incident responses, and system designs. Provide examples of how effective documentation has helped streamline workflows in your previous roles.

In your answer, focus on the influence of technical leadership through expertise rather than authority. Discuss how you establish technical standards, facilitate training sessions, and lead by example. Highlight your ability to inspire and motivate engineers through collaboration and knowledge sharing.

When discussing cloud infrastructure management, elaborate on the tools you're experienced with, such as Kubernetes, Terraform, or Google Cloud Platform. Explain which tools are suited for different tasks, such as deployment, scaling, or monitoring, and share examples of how you've utilized these tools effectively in past projects.

Describe a situation where you successfully balanced short-term project demands with longer-term goals in system architecture. Emphasize your decision-making process and how you weighed trade-offs, demonstrating your problem-solving skills and strategic thinking.

When answering this question, share your strategies for staying current in the fast-evolving field of data platform technologies. Mention any online courses, webinars, or industry conferences you attend, and discuss how you actively engage with communities or forums to exchange ideas and experiences with peers.