About the Role

We are seeking a highly skilled and experienced Data Developer to join our team at Citi. The successful candidate will be instrumental in designing, implementing, and optimizing scalable and efficient data solutions, primarily within the Hadoop ecosystem. This role requires a strong technical background, a deep understanding of big data technologies, and a commitment to best practices in data architecture, security, and performance.

Key Responsibilities

• Design and implement scalable and efficient Hadoop architecture solutions.

• Collaborate with data engineers and scientists to understand data requirements and translate them into robust data solutions.

• Optimize Hadoop clusters for performance and resource utilization, ensuring efficiency and cost-effectiveness.

• Maintain and monitor Hadoop infrastructure, ensuring high availability, reliability, and disaster recovery capabilities.

• Implement data security and governance policies to protect sensitive information and ensure compliance with regulatory standards.

• Stay updated with the latest advancements in Hadoop and big data technologies, evaluating and recommending new tools and practices.

• Troubleshoot and resolve complex issues within the Hadoop ecosystem, minimizing downtime and ensuring continuous operations.

• Responsible for developing Spark-based solutions to support near real-time data ingestion, analytics, and reporting needs.

Qualifications

• 3-8 years of relevant experience in the Financial Service industry.

• Consistently demonstrates clear and concise written and verbal communication.

• Demonstrated problem-solving and decision-making skills.

• Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements.

Required Skills and Experience

• Big Data Technologies:

  • Hadoop

  • HDFS (Hadoop Distributed File System)

  • YARN (Yet Another Resource Negotiator)

  • MapReduce

  • Hive

  • Spark

• Cloud Platforms:

  • AWS (Amazon Web Services)

  • Azure (Microsoft Azure)

  • Google Cloud

• Data Management:

  • Data modeling

  • ETL processes (Extract, Transform, Load)

  • Data warehousing

• Programming & Scripting:

  • SQL

Advanced Skills & Experience

• Proven experience in designing and managing Hadoop-based architectures.

• Strong understanding of Hadoop ecosystem components.

• Strong hands-on and architectural knowledge of Python, PySpark, and Unix.

• Exposure to AI/ML lifecycle management, MLOps, and GenAI solutions.