2 months ago
Base Salary
$142k - $213k/yr
Responsibilities
- Define and drive the technical vision, architecture, and roadmap for Citi’s enterprise data lake and analytics platform.
- Lead, mentor, and develop a team of data engineers while setting technical standards and conducting code and architecture reviews.
- Translate business and analytics requirements into scalable enterprise data platform capabilities.
- Design, build, deploy, and support production-grade batch and real-time streaming pipelines using Java-based technologies.
- Build and operate pipelines with Apache Iceberg, Starburst, Apache Pinot, Apache Kafka, and Apache Flink.
- Implement feature stores supporting model training and real-time machine learning inference.
- Optimize data storage, query performance, lakehouse architectures, and distributed data systems.
- Establish metadata management, data lineage, data quality, reconciliation, monitoring, and governance frameworks.
- Ensure platforms meet enterprise security, encryption, privacy, GDPR, and CCPA requirements.
- Evaluate emerging data technologies and drive improvements in scalability, reliability, operational excellence, and performance.
Requirements
- Bachelor’s degree, university degree, or equivalent professional experience in Computer Science, Data Engineering, Information Systems, or a quantitative field.
- At least 6 years of professional experience in data engineering, software engineering, or data platform development.
- At least 3 years of experience in a technical lead or engineering leadership role.
- Expert proficiency in Java and SQL; Python proficiency is highly desirable.
- Experience designing and building large-scale data transmission, ingestion, transformation, and processing pipelines.
- Deep expertise with Apache Iceberg, StarTree/Apache Pinot, Hive/HDFS, and distributed computing.
- Hands-on experience building and operating high-volume real-time streaming pipelines with Apache Kafka and Apache Flink.
- Experience building data infrastructure for machine learning, advanced analytics, or AI applications in production.
- Experience with Apache Iceberg, Delta Lake, or Apache Hudi and lakehouse architectures.
- Experience with Apache Airflow or equivalent workflow orchestration tools.
- Strong understanding of data governance, metadata, lineage, data quality, enterprise security, and distributed-system troubleshooting.
- Preferred qualifications include a master’s degree, Databricks experience, vector databases, dimensional modeling, Data Vault, Docker, Kubernetes, Terraform, enterprise data warehousing, and engineering-team mentorship.
Benefits
- Hybrid work model with 3 days in the office and 2 days working remotely in Jersey City, New Jersey.
- Continuous learning and professional development resources.
- Medical, dental, and vision coverage; 401(k); life, accident, and disability insurance; and wellness programs.
- Paid vacation, sick leave, and holidays.
- Wellbeing support and work-life balance programs.
- Competitive compensation and financial wellbeing benefits, with eligible discretionary and formulaic incentive and retention awards.
- Opportunity to lead enterprise-scale data and AI initiatives and collaborate with Data Scientists, AI Researchers, Enterprise Architects, and business leaders.
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.