Market Data Software Engineer

As a Market Data Software Engineer at Clear Street, your main responsibilities will involve designing, developing, and maintaining real-time data pipelines that handle financial market data efficiently. You'll work with various asset classes to ensure timely data processing and collaborate with different teams to understand their requirements. Your role will also include troubleshooting performance issues and ensuring data integrity across the pipelines, making your contributions critical to our data operations.

To qualify for the Market Data Software Engineer position at Clear Street, candidates should have at least 5 years of professional experience in implementing low-latency and high-throughput data pipelines. A solid understanding of distributed systems and familiarity with financial market data, including security prices, is essential. Proficiency in Linux/BSD, knowledge of TCP/IP networking, and excellent communication skills for collaboration are also important.

At Clear Street, the FACT team utilizes a diverse tech stack including C++, Rust, Go, Java, Python, gRPC, PostgreSQL, Snowflake, Kafka, and Kubernetes. Familiarity with these technologies, particularly those related to data handling and real-time processing, will be advantageous for a Market Data Software Engineer looking to join our team.

At Clear Street, we’re committed to providing our Market Data Software Engineers with opportunities for professional development and career growth. The environment encourages innovative ideas and offers responsibilities that can lead to advancement within a growing team. Whether you're aiming for a Senior role or looking to progress to a Staff-level position, the possibilities for growth here are prominent.

The working conditions for the Market Data Software Engineer at Clear Street blend modern office amenities with a strong emphasis on collaboration and teamwork. Our culture promotes healthy communication and support among employees, and we believe in the benefits of in-office involvement, encouraging our team to come together four days a week to foster a vibrant workplace atmosphere.

When answering this question, highlight specific projects where you've designed and implemented real-time data pipelines. Discuss the technologies you used and any challenges you overcame to ensure performance and reliability.

It's essential to discuss a step-by-step approach. Mention how you analyze logs, monitor data flow, and collaborate with other teams to pinpoint issues. Your ability to communicate effectively with cross-functional teams is key here.

To answer this effectively, explain your understanding of system architecture and techniques like optimizing algorithms, employing efficient data structures, and using appropriate networking protocols to minimize latency.

Here, elaborate on your experience with security prices, asset classes, and data models. Share specific examples of how you've worked with and manipulated financial data.

Share a specific instance and highlight the improvements you made. Discuss metrics that measured the enhancement, such as speed and efficiency, and the impact it had on your team's operations.

You should discuss specific monitoring tools and techniques you've employed, including how they helped you identify bottlenecks or performance issues and the subsequent actions you took to resolve them.

Discuss how you engage with the tech community, whether through attending conferences, participating in online forums, or following industry leaders. This shows your commitment to staying informed about advancements.

Highlight the programming languages listed in the job description, such as C++, Rust, or Python, and provide examples of how you've utilized these languages in building data processing solutions.

Provide a clear example where you collaborated with teams outside your own, such as trading or analytics, emphasizing your communication skills and how the collaboration contributed to project success.

Reflect on any challenges you experienced, such as data consistency or fault tolerance. Discuss how you approached these issues practically, demonstrating your ability to problem-solve effectively.