01Responsibilities
Helps to define and ongoing management of target data architecture for risk information.Liaises with other Citi risk organizations to identify and maintain appropriate alignment, specifically with Citi Data Standards.Works in conjunction with information owners and technology partners to define and implement the roadmap.Prepares materials for Monthly Operating Reviews (MORs), Portfolio Reviews, Horizontal meetings, Town Halls and Staff Meetings.Performs analysis of DQ issues and deliver metrics reporting.Supports Managers with status reports and presentation content. Guide data analysis and reporting processes that include collection from multiple sources, validation of data and assembly and presentation of required data.Develops new data collection and evaluation methodologies, including format design, data compilation, relevancy and metrics.Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.Integrates in-depth data analysis knowledge with a solid understanding of industry standards and practices.Demonstrates a Good understanding of how data analytics teams and area integrate with others in accomplishing objectives.Applies project management skills.Applies analytical thinking and knowledge of data analysis tools and methodologies.Establish and create data pipelines for retention, cleanup, persistence, and maintenance of data on NoSQL datastores.Implement data consistency checks and rules to ensure data meets business standards and needs.Optimize data engineering pipelines and queries to ensure efficiency, reliability and scalability of data processing and analysis.Perform root cause analysis on issues and processes to answer specific business questions and identify opportunities for improvement.
Qualifications:
8+ years Banking or Financial Services experienceExperience in analyzing and defining risk management data structures and architectureDemonstrated influencing, facilitation and partnering skillsTrack record of interfacing with and presenting results to senior managementAnalytical, flexible, team-oriented and have good interpersonal/communication skillsEngineers with 8+years of data engineering experience in Big Data ecosystem with primary skill as Spark.Experienced in data integration (ETL/ELT) and building scalable and maintainable data pipeline supporting a variety of integration patterns (batch, replication, event streaming).Strong knowledge on NoSQL DB - HBaseShould have basic knowledge on Bigdata Cluster and operationsSupport system migration programs including legacy-to-cloud transitions by conducting data mapping, reconciliation, and parallel run analysisStrong 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 Experienced in working on medium to large enterprise projects, preferably in financial servicesWillingness to experiment and learn new approaches and technology applicationsExcellent written and verbal communication skills
Education:
Bachelors/University degree or equivalent experience
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