Jobs at Citibank in Singapore

Whether you’re at the start of your career or looking to discover your next adventure, your story begins here. At Citi, you’ll have the opportunity to expand your skills and make a difference at one of the world’s most global banks. We’re fully committed to supporting your growth and development from the start with extensive on-the-job training and exposure to senior leaders, as well as more traditional learning. You’ll also have the chance to give back and make a positive impact where we live and work through volunteerism.

Citibank serves as a trusted advisor to our retail, mortgage, small business and wealth management clients at every stage of their financial journey. Through Citi's Access Account, Basic Banking, Citi Priority, Citigold and Citigold Private Client, we offer an array of products, services and digital capabilities to clients across the full spectrum of consumer banking needs worldwide.

We’re currently looking for a high caliber professional to join our team as Data Engineering Lead - Big Data Technologies - Vice President based in Singapore. Being part of our team means that we’ll provide you with the resources to meet your unique needs, empower you to make healthy decision and manage your financial well-being to help plan for your future. For instance:

The Data Engineering Lead is a senior level position responsible for leading a variety of engineering activities including the design, acquisition and deployment of hardware, software and network infrastructure in coordination with the Technology team. The overall objective of this role is to lead efforts to ensure quality standards are being met within existing and planned framework.

• Strategic Leadership: Define and execute the data engineering roadmap for Global Wealth Data, aligning with overall business objectives and technology strategy. This includes understanding the data needs of portfolio managers, investment advisors, and other stakeholders in the wealth management ecosystem.
• Team Management: Lead, mentor, and develop a high-performing, globally distributed team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.
• Architecture and Design: Oversee the design and implementation of robust and scalable data pipelines, data warehouses, and data lakes, ensuring data quality, integrity, and availability for global wealth data. This includes designing solutions for handling large volumes of structured and unstructured data from various sources.
• Technology Selection and Implementation: Evaluate and select appropriate technologies and tools for data engineering, staying abreast of industry best practices and emerging trends specific to wealth management data.
• Performance Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness, ensuring optimal access to global wealth data.
• Collaboration: Partner with business stakeholders, data scientists, portfolio managers, and other technology teams to understand data needs and deliver effective solutions that support investment strategies and client reporting.
• Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, security, and compliance with relevant regulations, particularly around sensitive financial data.

• 10-15 years of hands‑on experience in Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix Scripting and other Big data frameworks.
• 4+ years of experience with relational SQL and NoSQL databases: Oracle, MongoDB, HBase
• Strong proficiency in Python and Spark Java with knowledge of core spark concepts (RDDs, Dataframes, Spark Streaming, etc) and Scala and SQL
• Data Integration, Migration & Large Scale ETL experience (Common ETL platforms such as PySpark/DataStage/AbInitio etc.) — ETL design & build, handling, reconciliation and normalization
• Data Modeling experience (OLAP, OLTP, Logical/Physical Modeling, Normalization, knowledge on performance tuning)
• Experienced in working with large and multiple datasets and data warehouses
• Experience building and optimizing ‘big data’ data pipelines, architectures, and datasets.
• Strong analytic skills and experience working with unstructured datasets
• Ability to effectively use complex analytical, interpretive, and problem‑solving techniques
• Experience with Confluent Kafka, Redhat JBPM, CI/CD build pipelines and toolchain – Git, BitBucket, Jira
• Experience with external cloud platform such as OpenShift, AWS & GCP
• Experience with container technologies (Docker, Pivotal Cloud Foundry) and supporting frameworks (Kubernetes, OpenShift, Mesos)
• Experienced in integrating search solution with middleware & distributed messaging - Kafka
• Highly effective interpersonal and communication skills with tech/non‑tech stakeholders.
• Experienced in software development life cycle and good problem‑solving skills.
• Excellent problem‑solving skills and strong mathematical and analytical mindset
• Ability to work in a fast‑paced financial environment

• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred

Be conscientious and consistent in identifying security vulnerabilities and working with the respective engineering teams and stakeholders to provide sound guidance and remediations. Be a team player, and a keen learner.

Working at Citi is far more than just a job. A career with us means joining a family of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

https://jobs.citi.com/dei