Citi este o companie globală de servicii bancare și financiare care deservește consumatori, corporații, guverne și instituții. Oferta sa include servicii bancare pentru consumatori, carduri de credit, administrarea patrimoniului, servicii bancare pentru companii și servicii de investiții, susținute de operațiuni în peste 100 de țări. În calitate de mare organizație financiară internațională, Citi reunește echipe care activează în domeniul bancar, al serviciilor financiare și al tehnologiei financiare.
Senior Data Analytics Developer at Citi (Hybrid, Tampa)
Build Python analytics applications and data pipelines for Citi’s Prime Services technology. Help develop AI-enabled monitoring and support financial-data platforms and global production operations.
Descriere
- Build and maintain data analytics applications and pipelines, mainly in Python and Java.
- Use AI-assisted development tools to speed delivery and improve code quality.
- Help create AI-powered monitoring agents that improve operational visibility and automate routine production tasks.
- Develop and optimize data sourcing integrations for Prime Services and Markets Technology.
- Create analytics tools and dashboards for business users and quantitative analysts.
- Deliver tested, maintainable production code and take part in code reviews.
- Design scalable systems for high volumes of order, execution, trade, and position data.
- Build and maintain batch processing jobs and automated workflows.
- Investigate and resolve technical issues across the data platform.
- Build scalable data solutions with Trino/Starburst, S3, Kafka, and Spark.
- Support production processes and batch jobs during Asia morning hours.
- Coordinate operational handoffs and continuity with teams in the US and UK.
- Support monitoring, alerting, incident response, operational resilience, and business continuity.
- Identify root causes and implement lasting fixes.
- Work with business subject matter experts and quantitative analysts to understand data and analytics needs.
- Turn complex business needs into technical specifications and engineering solutions.
- Create reusable solutions for recurring data requirements.
- Support data visualization and analytics reporting platforms.
- Maintain data accuracy, completeness, and timeliness.
- Implement and monitor data quality rules, validation frameworks, and remediation processes.
- Document metadata and data lineage.
- Follow enterprise data standards and regulatory requirements.
Cerințe
- Bring 8–10 years of experience in software engineering, data engineering, or data analytics in banking or financial services.
- Have a strong hands-on engineering background designing, building, and maintaining production data systems as an individual contributor.
- Have experience with modern AI-assisted development and testing tools such as GitHub Copilot, Devin, or Claude.
- Experience building or contributing to AI-powered agents for monitoring, alerting, or workflow automation is strongly preferred.
- Understand Markets financial data, including orders, executions, trade processing, position management, and related trade lifecycle data.
- Have worked directly with quantitative analysts and business stakeholders to turn requirements into technical solutions.
- Have supported global production environments, including off-hours batch processing and operational support.
- Have strong practical Python skills.
- Knowledge of Java is an advantage.
- Familiarity with Trino/Starburst, S3, Kafka, and Spark is highly preferred.
- Be proficient with AI-assisted coding and testing tools, with practical experience designing and building LLM-powered or agent-based operational solutions.
- Understand enterprise and open-source data ingestion and distribution frameworks.
- Have a solid grasp of Markets financial data, including P&L, risk, and reference data.
- Have experience with Kafka and Gemfire or Redis.
- Be proficient in SQL and relational and NoSQL database management systems.
- Have experience designing and managing batch jobs, schedulers, and workflow orchestration tools.
- Have experience with data quality frameworks, validation methods, and remediation strategies.
- Be familiar with CI/CD pipelines, containerization, and deployment automation.
- Communicate effectively in writing and verbally.
- Be able to work with quantitative analysts and business subject matter experts to understand complex data requirements.
- Work effectively with diverse teams across global locations.
- Be able to work under pressure, facilitate discussions, and contribute constructively to group meetings.
- Bring strong diplomacy skills.
- Have a bachelor's degree or equivalent experience; a background in Computer Science, Information Systems, Mathematics, Statistics, Engineering, or another quantitative field is preferred.
- A master's degree or advanced certification in a relevant field is preferred.
Beneficii
- Discretionary and formula-based incentive and retention awards.
- Medical, dental, and vision coverage.
- 401(k) plan.
- Life, accident, and disability insurance.
- Wellness programs.
- Paid time off, including planned vacation, sick leave, and paid holidays.