Senior Software Engineer, Post-Trade Financial Systems
Develops scalable data infrastructure, real-time processing systems, and observability tools for post-trade financial systems supporting AI/ML-driven trading. Requires 5+ years experience with Python, data engineering, and cross-functional leadership in high-stakes production environments.
225k – 255k
Hybrid5+ YOEData Engineering
About the role
Responsibilities
Design and optimize robust, scalable data infrastructure and real-time stream processing systems to support historical and live pipelines using tools like Python, Airflow, Go, and Apache Beam.
Develop and maintain observability and remediation tools to monitor and analyze trading performance and risk, ensuring reliability and transparency in operations.
Lead efforts to integrate new financial assets and markets, clarifying requirements and ensuring seamless functionality within existing systems.
Enhance the resilience, scalability, and performance of accounting and reporting systems to meet evolving business needs.
Build advanced tooling to unify data from diverse vendors, standardizing symbol mappings to ensure consistency and accuracy across systems.
Lead complex, company-wide projects by collaborating cross-functionally with research, legal, trading, finance operations, data, and infrastructure teams to deliver comprehensive end-to-end accounting and reporting systems.
Build the infrastructure required for optimal extraction, transformation, and loading of data from various data sources.
Guide and support the growth of other engineers on the team by mentoring them and sharing your expertise, best practices, and knowledge.
Requirements
Bachelor’s degree in Computer Science or equivalent professional experience in a related technical field.
5+ years of software engineering experience designing and building high-performance, reliable systems.
Proven expertise in operating and scaling large-scale, mission-critical production systems, with proficiency in programming languages such as Python.
Strong communication and project management skills, particularly in navigating complex technical domains and cross-functional collaboration.
Demonstrated ability to mentor engineers and provide leadership in driving technical direction and system architecture.
Preferred Qualifications
Expertise in building and optimizing data pipelines (e.g. Change data capture, data modeling, data streaming, etc.).
Experience with profiling and performance optimizations on distributed systems.
Familiarity with modern Python data science tooling (pandas, polars, dask, duckdb, etc.).
Experience with modern data engineering technologies.
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