A financial firm is looking for a Lead KDB Engineer to join their team in New York, NY. 

Compensation: $200k base bonus 

Responsibilities:

Design, develop, and maintain kdb databases and risk engine components. Develop solutions in Q/kdb , Python/PyKX to enhance market risk data processing. Implement scalable and high-performance computing solutions for market risk analytics. Collaborate with cross-functional teams and global counterparts to deliver high-quality solutions. Optimize risk data processing pipelines to improve efficiency and response time. Ensure compliance with regulatory requirements for market risk technology. Work in an Agile development environment, ensuring timely and efficient product delivery. Provide technical leadership and mentorship to junior developers in the squad. Troubleshoot and resolve performance issues within KDB and risk analytics platforms.

Qualifications:
Required

Hands-on experience with kdb /Q. Proficiency in Python and PyKX for data analytics and processing. Experience in designing and building large-scale business-critical systems. Strong fundamentals in data structures and algorithms. Ability to understand market risk domain and its data and implement efficient data solutions. Strong problem-solving and analytical thinking. Ability to act autonomously in complex decision-making. Capacity to develop and manage operational initiatives that align with business goals. Good communication skills. Must be comfortable and effective working independently (team is global - mostly in Budapest, with some presence in NY & Montreal). 5 years of designing and building apps - building distributed systems is a plus.

Preferred

Experience with Java, kdb Insights a plus. Architectural understanding of kdb and distributed computing. Exposure to big data technologies such as Apache Spark. Familiarity with Agile software development and DevOps best practices. Experience with cloud technologies such as AWS, Azure, or Google Cloud Platform (GCP). Knowledge of cloud-based data processing frameworks and containerized deployments (Docker, Kubernetes). Experience with Financial technologies (FinTech) or background in finance.