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Senior Big Data Engineer - Assistant Vice President

India, Pune · Job Posted May 11, 2026
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Job Description

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
  • Technical Skillset: Programming Languages: Java (primary), Shell Scripting
  • Data Querying & Databases: SQL (strong proficiency), Oracle (database management & optimization)
  • Big Data Ecosystem: Apache Spark, Spark Streaming, Hadoop
  • Backend Frameworks: Spring Boot, JPA (Java Persistence API)
  • Event-Driven Architecture: Apache Kafka (real-time streaming & data ingestion)
  • Job Scheduling & Automation: Autosys (enterprise workload automation)
  • Data Platforms: Data Warehouse concepts and architectures

Nice to have

  • Experience with NoSQL data models (e.g., MongoDB, Couchbase) for analytical use cases
  • Familiarity with in-memory caching technologies such as Redis or Couchbase
  • Proficiency in Python (PySpark) for supplementary data manipulation and analysis tasks
  • Knowledge of cloud-based data platforms (AWS, Azure, or GCP) and their data services
  • Exposure to CI/CD pipelines and DevOps practices for data engineering workflows
  • Experience with data governance frameworks and data quality management tooling
  • Familiarity with containerization technologies such as Docker or Kubernetes
  • Understanding of RESTful API design and microservices architecture patterns
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