1 day ago
Pune, IndiaStaff+
Responsibilities
- Design and implement high-throughput, low-latency Python backend services and SQL pipelines for financial market data.
- Translate regulatory mandates and market surveillance policies into deterministic control algorithms and automated surveillance engines.
- Model trade lifecycles, order workflows, executions, and multi-asset risk analytics with trading, risk, and compliance stakeholders.
- Perform application profiling, database tuning, indexing, and SQL query optimization to improve latency and throughput.
- Implement Generative AI-assisted solutions and automation to reduce manual operational work and streamline control testing.
- Lead architectural decisions, system design reviews, peer code reviews, testing standards, and engineering best practices.
- Use GitHub and Jira for modern CI/CD practices and mentor engineers across the team.
- Ensure deliverables comply with engineering policies, enterprise security standards, and global regulatory requirements.
Requirements
- 10+ years of professional software engineering experience building backend applications and data-intensive pipelines in Python.
- Advanced SQL expertise, including relational database design, query optimization, indexing strategies, and database performance profiling.
- Strong investment banking and capital markets knowledge, including trade and transaction lifecycles, order management, execution workflows, and market risk analytics.
- Demonstrated technical leadership through architectural reviews, mentoring, and setting engineering standards.
- Strong analytical, problem-solving, communication, and stakeholder-alignment skills.
- Bachelor’s or university degree, or equivalent professional experience; a master’s degree is preferred.
- Prior experience with regulatory reporting or market surveillance platforms such as MiFID II, CAT, Dodd-Frank, MAR, or Best Execution is beneficial.
- Experience with Docker, Kubernetes, or OpenShift is beneficial.
- Exposure to Apache Spark, PySpark, Kafka, Solace, or MQ is beneficial.
- Experience applying Generative AI APIs, prompt engineering, or LLM-driven tooling is beneficial.
Benefits
- Hybrid working model combining remote work with in-office collaboration in Pune.
- Access to comprehensive technical training and leadership growth programs across Citi’s global engineering community.
- Direct technical ownership of critical systems supporting market integrity and regulatory compliance.
Tech Stack
Categories
BackendData Engineering
About Citi
Citi is a public financial-services company offering consumer and institutional banking, credit cards, wealth management, treasury and trade solutions, and capital-markets services. It serves individuals, corporations, financial institutions, and governments in more than 160 countries and jurisdictions, earning interest and fee income from lending, payments, trading, and advisory. Founded in 1812 and headquartered in New York, it trades on the NYSE under the ticker C.