Data Analytics Cloud Group Manager - Senior Vice President
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Job Overview
The Data Analytics Cloud Group Manager is accountable for management of complex / critical / large professional disciplinary areas. Leads and directs a team of professionals. Requires a comprehensive understanding of multiple areas within a function and how they interact in order to achieve the objectives of the function. Applies in-depth understanding of the business impact of technical contributions. Strong commercial awareness is a necessity. Generally accountable for delivery of a full range of services to one or more businesses / geographic regions. Excellent communication skills required in order to negotiate internally, often at a senior level. Some external communication may be necessary. Accountable for the end results of an area. Exercises control over resources, policy formulation and planning. Primarily affects a sub-function. Involved in short- to medium-term planning of actions and resources for own area. Full management responsibility of a team or multiple teams, including management of people, budget and planning, to include performance evaluation, compensation, hiring, disciplinary actions and terminations and budget approval.
Responsibilities :
- Accountable for all products as well as designing and implementing both the tactical and strategic data.
- Serves as the subject matter expert for strategic data analysis, identifies insights and implications, as well as make strategic recommendations and develop data displays that clearly communicate complex analysis.
- Defines the service model for each new incubated data product or data product set across the various businesses and regions.
- Prepares and presents key business cases underpinning strategic investment initiatives to maintain or build out the product capability.
- Participates in strategic business engagements to build the right level of data inclusion into all business forums below the top executive level.
- Plans and manages on-going product investment and activity in-line with defined portfolio balance, capacity, and capability planning and development.
- Builds a product improvement & innovation pipeline for prioritization and build an initial view of the underlying commercial value and potential.
- Ensures current product landscape and architecture is mapped out, and deeply understood from a product origination point through fulfillment, processing, billing, servicing, and revenue realization and reporting.
- Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firms 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.
- Serve as an advisor and coach for developers, analysts, and new team members, fostering their growth and development in areas such as GenAI, Spark, AWS cloud services, and big data technologies.
Required Qualifications :
At least 10+ years experience in software or data engineering space.At least 5 years experience with Data lake infrastructure, data warehousing, and data pipelines design - Hadoop, Spark, Python, Scala.Cloud-Native Architectures (AWS EKS, S3) : Architecting and managing scalable, resilient applications on AWS, specifically utilizing Amazon EKS for container orchestration and Amazon S3 for robust, cost-effective object storage and data lakes.At least 3 years experience with all aspects of DevOps (Source control, CICD etc.) Experience with containerization technologies (Docker, Kubernetes) is preferred. Experience in building data pipelines and applications in public cloud (AWS, Snowflake) is strongly preferred.Experience in ML Designing, developing, and integrating ML models and applications, understanding their lifecycle, ethical implications, and performance optimization.At least 3 years experience in data governance platforms, data standardization, and data modeling.Preferred Qualifications :
Complex Problem Solving : Analyze intricate business and system processes, alongside industry standards, to define and develop high-level solutions, including those involving large-scale data processing and machine learning.Advanced Programming Expertise : Provide expert-level knowledge in applications programming, particularly for large-budget, cross-functional, or multiple concurrent projects. This includes hands-on experience with :Apache Spark : Implementing efficient data processing pipelines for big data analytics, machine learning workflows, and real-time data streams.Data Quality & Governance (Hadoop Ecosystem) : Ensuring high data quality standards across diverse datasets, leveraging tools and principles within the Hadoop ecosystem for data management, validation, and transformation.Education :
Bachelors / University degree or equivalent experience, potentially Masters degree.