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The Senior Data Engineer (C12 – AVP) is a senior-level position responsible for liaising between business users and technologists to analyze complex datasets, derive actionable insights, and support data-driven decision-making. The overall objective of this role is to perform in-depth data exploration, define data requirements, and contribute to the development of robust data solutions in close coordination with the Technology team. The ideal candidate will bring deep technical expertise across big data ecosystems, enterprise-grade development frameworks, and data pipeline engineering, while demonstrating strong business acumen and stakeholder management capabilities within the Financial Services or Banking domain.
Job Responsibility:
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
Design and implement scalable data pipelines and batch/streaming workflows using Apache Spark, Spark Streaming, Hive, and Hadoop within enterprise big data ecosystems
Develop and maintain backend services and automation scripts using Java, Spring Boot, JPA, and Shell Scripting to support data processing and operational workflows
Build and manage event-driven data architectures leveraging Apache Kafka for real-time data ingestion and streaming use cases
Automate job scheduling and dependency management using Autosys
manage and optimize Oracle database objects and queries to support analytical workloads
Develop supporting interfaces and data visualization components using JavaScript to enhance data accessibility and reporting capabilities
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 collaborate effectively 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 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
Requirements:
9–12 years of relevant experience in data analysis and data engineering, 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
Education: Bachelor's degree / University degree in a technical or business discipline (Computer Science, Information Systems, Engineering, Finance, or equivalent experience)
Functional Skillset: Data Analysis: Extensive experience in analyzing and interpreting complex data from disparate sources to provide actionable insights
Financial/Banking Domain Expertise: Strong understanding of financial products, banking processes, and industry standards
Data Requirements Definition: Proven ability to analyze different data sources and datasets to create comprehensive data mapping documents and define data ingestion requirements
Stakeholder Management: Ability to create and deliver presentations for senior management and effectively manage stakeholder expectations
SDLC: Experience with all phases of the Software Development Life Cycle (SDLC), particularly in requirements gathering, design, and testing