21 hours ago
Hong Kong, Hong KongStaff+
Responsibilities
- Design, develop, and maintain data analytics applications and pipelines primarily with Python and Java.
- Build data-sourcing integrations, analytics tools, dashboards, batch jobs, automated workflows, and data-distribution solutions.
- Architect scalable solutions for large volumes of orders, executions, trades, positions, and related financial data.
- Use data mesh, object storage, streaming, and distributed-processing technologies to build performant data platforms.
- Develop and contribute to AI-powered monitoring agents and automated production workflows using AI-assisted development tools.
- Support global production processes, batch jobs, monitoring, alerting, incident response, root-cause analysis, and operational continuity.
- Partner with quantitative analysts, business SMEs, Markets teams, and technology stakeholders to gather requirements and deliver reusable solutions.
- Implement data-quality rules, validation and remediation processes, metadata, data lineage, and enterprise data standards.
- Support data visualization and analytics reporting capabilities.
Requirements
- 8–10 years of experience in software engineering, data engineering, or data analytics within banking or financial services.
- Strong hands-on experience designing, building, and maintaining production-grade data systems as an individual contributor.
- Strong Python proficiency; Java knowledge is a plus for existing JVM-based services.
- Experience with modern AI-assisted coding and testing tools such as GitHub Copilot, Devin, or Claude; experience building AI-powered agents is strongly preferred.
- Strong knowledge of Markets financial data, including orders, executions, trade processing, positions, P&L, risk, and reference data; Prime Services or Prime Brokerage experience is a plus.
- Experience working with quantitative analysts and business stakeholders to translate requirements into technical solutions.
- Experience supporting globally distributed production environments and off-hours batch processing.
- Familiarity with Trino/Starburst, S3, Kafka, and Spark is highly preferred.
- Knowledge of data ingestion and distribution frameworks, distributed systems, SQL, relational and NoSQL databases, batch processing, schedulers, workflow orchestration, data-quality frameworks, and data-platform architecture.
- Experience with Gemfire or Redis, CI/CD pipelines, containerization, deployment automation, data lakes, data warehouses, analytics platforms, and data visualization tools is relevant or preferred.
- Bachelor’s or university degree, or equivalent experience, preferably in computer science, information systems, mathematics, statistics, engineering, or a related quantitative field.
- Excellent communication, diplomacy, collaboration, and stakeholder-management skills across globally distributed business and technology teams.
- A master’s degree or relevant advanced certifications is preferred.
Benefits
- Full-time position within Citi’s Technology organization.
- Global team environment spanning the US and UK, with production support for batch processes during Asia morning hours.
- Equal opportunity employer with reasonable accommodation support for applicants with disabilities.
Tech Stack
Categories
Data 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.