Senior Bigdata Engineer -Assistant Vice President

• Formulate and define the scope and objectives for complex data analysis projects, fostering clear communication between business leaders and IT
• Consult with users and clients to solve complex data-related issues through in-depth evaluation of business processes, data sources, and industry standards
• Analyze large and diverse datasets from various sources to identify trends, patterns, and anomalies, providing critical input for business and technology initiatives
• Develop and document data mapping specifications, transformation logic, and ingestion requirements for new data pipelines and systems
• Consult with business clients to determine functional specifications for data-centric systems and provide ongoing operational support
• Identify, communicate, and mitigate risks and impacts related to data quality, data governance, and the application of technology
• Act as an advisor or coach to new or lower-level analysts and work as a team to achieve business objectives
• Act as a Subject Matter Expert (SME) on data sources, data models, and analysis techniques for senior stakeholders and other team members
• 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

• 8-12 years of relevant experience in data analysis, preferably within the Financial Services or Banking industry
• Proven interpersonal, diplomatic, management, and prioritization skills
• Consistently demonstrates clear and concise written and verbal communication
• Proven ability to manage multiple activities, build strong working relationships, and work effectively under pressure
• Demonstrated strong problem-solving, analytical, and decision-making skills with a methodical attention to detail
• Proven self-motivation to take initiative and master new tasks and technologies quickly
• Bachelor's degree/University degree in a technical or business discipline (or equivalent experience)
• Extensive experience in analyzing and interpreting complex data from disparate sources to provide actionable insights
• Strong understanding of financial products, banking processes, and industry standards
• Proven ability to analyze different data sources and datasets to create comprehensive data mapping documents and define data ingestion requirements
• Ability to create and deliver presentations for senior management and effectively manage stakeholder expectations
• Experience with all phases of the Software Development Life Cycle (SDLC), particularly in requirements gathering and testing
• Strong proficiency in SQL for querying relational databases and experience analyzing NoSQL data models (e.g., MongoDB, Couchbase)
• Hands-on experience with BigData ecosystems, including Apache Spark (using Python/PySpark or Java)
• Proficiency in Python for data manipulation and analysis
• Understanding of Data Warehouse concepts and architectures
• Knowledge of event-driven systems and technologies like Apache Kafka
• Familiarity with in-memory Caching technologies such as Redis or Couchbase

Familiarity with Java and Springboot