Software Engineer | Python & SQL Development | Experienced Hire
Overview
We are looking for a Software Engineer to join our Inbound Clearing team, where you will be a hands-on contributor building the systems that support firmwide inbound clearing workflows, data pipelines, and real-time operational visibility. This role sits at the intersection of technology, financial operations, and treasury workflows, ensuring the firm has accurate, timely, and normalized data to support downstream reporting, reconciliation, and decision-making.
You will partner closely with Operations, Treasury, Trading, and cross-functional engineering teams to modernize the data feeds and inbound clearing processes that power firmwide reporting. Much of your work will focus on improving system resiliency, re-architecting legacy pipelines, and enhancing transparency through better analytics tooling — systems where correctness is not optional and your output is consumed daily by the business.
An ideal candidate brings strong Python and SQL fundamentals, a positive attitude, a passion for solving problems and adding value however possible, and a strong desire to learn the business.
Platform & Project Work
- Re-architect and enhance inbound clearing pipelines to normalize data across all asset classes, products, and clearing venues
- Develop and maintain automated reporting tools related to financing, margin, cash movements, and exposure
- Drive reconciliation and data quality initiatives to ensure accuracy across positions, balances, and trades
- Collaborate with stakeholders to gather requirements and iterate quickly on enhancements to the clearing and reporting platform
- Use AI-assisted development tooling actively to improve delivery quality and velocity
Operational Support
- Support daily clearing workflows and ensure the accuracy of inbound data used for P&L, financing, RWA, margin, and regulatory reporting
- Troubleshoot data irregularities and partner with Operations to resolve breaks or inconsistencies before they reach the business
What we’re looking for
Technical Skills
- 3–6 years of hands-on development experience with strong Python and SQL fundamentals
- Comfort designing and querying large, structured datasets; experience building data pipelines or data-intensive services
- Experience building high-correctness systems where data accuracy matters — reconciliation, reporting, or similar
- Strong analytical and problem-solving skills, with attention to detail and a proactive approach to improving legacy processes
- Ability to work independently on multiple projects while maintaining close communication with business stakeholders
- Excellent communication skills for interacting with cross-functional teams and senior management
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Finance, or a related field (relevant experience may substitute for education)
Preferred Qualifications
- Experience within clearing, settlements, treasury, or other financial operations domains
- Exposure to large-scale data platforms or distributed systems (e.g., Hadoop, HBase, Druid)
- A desire to automate manual workflows and build robust, transparent operational systems
Why This Role
- Work on systems that matter: your pipelines and reporting are consumed daily by Operations, Treasury, and the business, and accuracy is paramount
- Real end-to-end ownership — you won’t be handed narrow tasks; you’ll own meaningful pieces of the clearing and reporting platform
- Opportunity to build, not just maintain — we are actively modernizing legacy pipelines and expanding analytics tooling
- A non-hierarchical, collaborative environment that empowers developers to make direct business impact
- Work in an environment that actively invests in AI tooling and expects engineers to use it
About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
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