Citi Group Data Lead L3 Manager 

India, Maharashtra, Pune 

771336524

Responsibilities:

• Manage one or more Applications Development teams in an effort to accomplish established goals as well as conduct personnel duties for team (e.g. performance evaluations, hiring and disciplinary actions)
• Utilize in-depth knowledge and skills across multiple Applications Development areas to provide technical oversight across systems and applications
• Review and analyze proposed technical solutions for projects
• Contribute to formulation of strategies for applications development and other functional areas
• Develop comprehensive knowledge of how areas of business integrate to accomplish business goals
• Provide evaluative judgment based on analysis of factual data in complicated and unique situations
• Impact the Applications Development area through monitoring delivery of end results, participate in budget management, and handling day-to-day staff management issues, including resource management and allocation of work within the team/project
• Ensure essential procedures are followed and contribute to defining standards negotiating with external parties when necessary
• 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, as well as effectively supervise the activity of others and create accountability with those who fail to maintain these standards.

Qualifications:

• 10-18 years of relevant experience in the Financial Service industry
• Experience as Applications Development Manager
• Experience as senior level in an Applications Development role
• Stakeholder and people management experience
• Demonstrated leadership skills
• Proven project management skills
• Basic knowledge of industry practices and standards
• Consistently demonstrates clear and concise written and verbal communication

Education:

• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.

Key Responsibilities
• Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources.
• Big Data Infrastructure: Develop and manage large-scale data processing systems using frameworks like Apache Spark, Hadoop, and Kafka.
• Cloud Integration: Implement data solutions on cloud platforms such as AWS, Azure, or Google Cloud.
• Data Modeling & Optimization: Design and optimize data models for efficient storage, retrieval, and analysis.
• Collaboration: Work closely with data scientists, analysts, and product teams to understand data requirements and deliver scalable solutions.
• Monitoring & Performance: Implement monitoring tools to track data pipeline performance and ensure data integrity.
• Security & Compliance: Ensure data security, governance, and compliance with internal and external standards.
• Mentorship: Guide junior engineers, provide technical leadership, and contribute to best practices.
• Proficiency in programming languages like Python, Java, or Scala.
• Strong expertise in data processing frameworks such as Apache Spark, Hadoop, or Flink.
• Experience with cloud data platforms like AWS (Glue, EMR, Redshift), Azure (Synapse), or GCP (BigQuery).
• Expertise in SQL and database technologies (e.g., Snowflake, PostgreSQL, etc.).
• Experience with data orchestration tools like Apache Airflow, Dagster, or Prefect.
• Familiarity with containerization (Docker, Kubernetes) is a plus.Preferred Qualifications
• Experience in real-time data processing and streaming platforms like Kafka, Kinesis, or Pulsar.
• Knowledge of CI/CD pipelines and Infrastructure as Code (e.g., Terraform, CloudFormation).
• Familiarity with machine learning pipelines and data science workflows.

Time Type:

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