About CITI 

Citi, the world leading global bank, has approximately 200 million customer accounts and a presence in more than 160 countries and jurisdictions worldwide. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management. Citi enables clients to achieve their strategic financial objectives by providing them with cutting-edge ideas, best-in-class products and solutions, and unparalleled access to capital and liquidity. A critical enabler of Citi’s mission to enable growth and economic progress is technology. Our teams are creating innovations used across the globe – we’re changing the way people bank and how the world does business.

Who We Are:

Citi’s Global Workforce Optimization (GWFO) is an organization within Citi’s Enterprise of Excellence. Enterprise Excellence designs solutions providing transparency & visibility of the current state; empowers operations and functions to leverage enterprise solutions to drive improved process & workforce optimization; and supports the evolution of the organization via continuous improvement & simplification. Our GWFO mission is to partner with Citi businesses globally to improve the customer experience, increase revenue, achieve service objectives, and maximize efficiency. GWFO support includes workforce management related activities, including capacity planning, analytics, and supplier tools support. Across the Citi Enterprise, we strive to:

• Drive workforce strategy and provide insights across capacity planning and supported applications to optimize people and processes
• Enable discipline, create consistency, and vigorously improve processes
• Deliver & optimize applications and tools in real-time while driving control rigor
• Serve as a trusted partner and subject matter expert supporting key strategic work

Overview:

Citi’s Enterprise Excellence team is seeking a detail-oriented Data Architecture Analyst with a strong focus on data lineage, modeling, and governance. This role is critical in ensuring the accuracy, consistency, and reliability of enterprise data assets while contributing to operational efficiency and compliance. The ideal candidate will have a technical foundation in data management, experience with data lineage & modeling tools, and a collaborative mindset to support cross-functional initiatives. Additionally, the candidate will have opportunities to incorporate data for innovative AI solutions while ensuring controls are established and will be part of the journey for data modernization for GWFO client needs.

Key Responsibilities:

• Data Lineage & Modeling:
  • Analyze and document the flow of data across systems and processes.
  • Develop and maintain detailed data lineage diagrams to trace data from source to destination.
  • Model data elements to business processes, ensuring alignment with organizational goals.
  • Collaborate with system architects and data engineers to enhance lineage visibility.
• Data Governance:
  • Maintain a comprehensive data dictionary and metadata repository.
  • Partner with stakeholders to ensure data compliance with regulatory requirements.
• Data Quality & Monitoring:
  • Conduct root-cause analysis on data inconsistencies and propose corrective actions.
  • Develop and implement data quality rules, metrics, and dashboards.
• Process Improvement & Collaboration:
  • Provide recommendations to streamline data workflows to improve operational efficiency.
  • Evaluate and recommend tools and technologies to enhance data lineage tracking and governance.
  • Utilize no code/low code tools to help drive automation.
  • Leverage a variety of data tools to simplify the data journey end to end with both technology and business partners.

Technical Skills:

• Proficiency in data querying languages (e.g. SQL/Python), transformation, and optimization.
• Experience with data lineage tools (e.g., Collibra, Informatica, Alation) and metadata management platforms.
• Familiarity with ETL processes and tools like Autosys, Talend, or Kafka.
• Knowledge of cloud data platforms (e.g., AWS, GCP, Azure) and data warehouses (e.g., Teradata, Hadoop, Snowflake).
• Experience with JIRA, Confluence, or similar platforms for task and project management.

Qualifications:

• 1-3 years of experience in data analysis, data governance, or related fields. Preferably in Banking or Financial Services industry.
• Demonstrated expertise in data lineage documentation and metadata management.
• Strong analytical and problem-solving skills, with a focus on accuracy and attention to detail.
• Excellent communication skills are a must to convey technical concepts to non-technical stakeholders.
• Ability to work independently and manage multiple priorities in a fast-paced environment.

Education:

• Bachelor’s degree in Data Science, Computer Science, Information Systems, or a related field (or equivalent experience).

This requisition is not VISA sponsorship eligible.