Market Data Software Engineer

As a Market Data Software Engineer at Clear Street, your primary responsibilities include designing, developing, and maintaining real-time data pipelines that efficiently handle financial market data with low latency and high throughput. You'll work closely with various financial instruments, ensuring accurate data processing while collaborating with product, trading, and risk teams to meet business requirements.

To be considered for the Market Data Software Engineer role at Clear Street, candidates should possess a minimum of 5 years of experience in implementing low-latency, high-throughput data pipelines. A solid understanding of distributed systems, familiarity with financial market data, and proficiency in Linux/BSD and TCP/IP networking are also essential. Strong collaborative skills and a keen eye for detail are highly valued.

A Market Data Software Engineer at Clear Street should have solid experience with programming languages and technologies such as C++, Rust, Go, Java, and Python. Knowledge of tools and frameworks like gRPC, PostgreSQL, Snowflake, Kafka, and Kubernetes will also be beneficial for managing real-time data processes efficiently.

At Clear Street, we foster a collaborative and meritocratic culture where your contributions matter. We promote an environment embracing DevOps principles alongside continuous integration and delivery methodologies, ensuring our teams work together towards common goals while continuously improving and innovating.

As a Market Data Software Engineer at Clear Street, you’ll have the chance to advance your career significantly within our growing firm. Depending on your experience and skills, you could rise through the ranks to Senior or Staff-level positions, contributing more to strategic projects and shaping our data offerings.

When answering this question, provide specific examples of projects where you've successfully designed and implemented low-latency data systems. Highlight the tools and technologies you utilized, the challenges you faced, and how you optimized performance to ensure rapid data processing.

Discuss your approach to maintaining data integrity, including strategies such as implementing robust error-handling mechanisms, conducting data consistency checks, and utilizing logging to monitor data processes effectively. Sharing an example can strengthen your response.

Emphasize your communication and teamwork skills. Provide an instance that showcases how you've successfully collaborated with product managers, traders, or risk teams to deliver data products that meet business needs, illustrating the importance of aligning technical efforts with organizational goals.

In your response, mention specific tools that are effective for monitoring system performance, such as Grafana, Prometheus, or custom dashboards. Discuss how you've used these tools to identify bottlenecks, resolve issues, and improve the overall efficiency of data pipelines.

Use the STAR method (Situation, Task, Action, Result) to detail a significant challenge, your responsibilities in that situation, the specific actions you took to address it, and the positive outcomes that resulted from your efforts.

Discuss strategies like parallel processing, efficient batching of data, or making use of distributed systems architectures that you've employed to maximize data throughput. Provide examples of improvements in processing speed you’ve achieved through these strategies.

Outline your experience and understanding of the financial market data structures relevant to the job, such as security prices, asset classes, and market data feeds. You can mention any specific projects that enhanced your knowledge of these structures.

Share examples of how you’ve integrated market data feeds, highlighting the tools and methods utilized, such as APIs or message queues. Emphasize your ability to troubleshoot and resolve discrepancies in real-time data processing.

Be specific about your proficiency in programming languages that are relevant to the Market Data Software Engineer position. Describe projects where you effectively used these languages to implement solutions related to financial data processing and the impact it had on your team's operations.

Your answer should showcase your enthusiasm for the company’s mission and culture. Highlight how your values align with Clear Street's innovative approach to finance and the opportunity for personal and professional growth within a collaborative team.