Java Lead (Java, Spring Boot Kafka) Data Analyst

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Job Overview

The Engineering Lead Analyst is a senior level position responsible for leading a variety of engineering activities including the design, acquisition and deployment of hardware, software and network infrastructure in coordination with the Technology team. The overall objective of this role is to lead efforts to ensure quality standards are being met within existing and planned framework.

Responsibilities:

• Serve as a technology subject matter expert for internal and external stakeholders and provide direction for all firm mandated controls and compliance initiatives, all projects within the group and in creating a technology domain roadmap
• Ensure that all integration of functions meet business goals
• Define necessary system enhancements to deploy new products and process enhancements
• Recommend product customization for system integration
• Identify problem causality, business impact and root causes
• Exhibit knowledge of how own specialty area contributes to the business and apply knowledge of competitors, products and services
• Advise or mentor junior team members
• Impact the engineering function by influencing decisions through advice, counsel or facilitating services
• 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.
• You will make contributions to the ideal architecture of the software
• Drive adoption of capabilities across regions by partnering with regional business and technology teams
• You will contribute to the microservice architecture development including RESTAPI and Graphql
• Develop approaches to integrate data into the DataHub (EAP) and prototype methods of developing insights on that data with our business analytics teams and digital product teams.
• Assist in troubleshooting Data and Client experience issues by leveraging our capabilities and / or working with other teams to dive into root cause analysis.
• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Cloud ‘big data’ technologies.
• Participate in all team ceremonies including planning, grooming, product demonstration and team retrospectives.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS/GCP regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data system.
• Ability to adjust priorities quickly as circumstances dictate
• Software must to have-
  • HBase
  • Mongo DB
  • Oracle
  • CICD
  • Light speed
  • OpenShift
  • ML /AL
  • ·Java
  • Java Microservice
  • Python
  • PySpark
  • Hadoop
  • Google
  • AWS

Qualifications:

• Languages: Java (expert), Python (proficiency is a plus)
• Frameworks: Spring Boot (deep expertise), Java Microservices, REST API, GraphQL
• Messaging/Streaming: Apache Kafka (deep expertise in design, development, and operation)
• Databases: HBase, MongoDB, Oracle, SQL
• DevOps/CI/CD: Experience with CI/CD pipelines, OpenShift, Git
• Big Data: Hadoop, PySpark (experience with real-time streaming and stream processing frameworks is a plus)
• Cloud Platforms: AWS, Google Cloud (GCP)
• Other: LightSpeed (experience is a plus), ML/AL concepts (awareness is a plus)

Education:

• Bachelor’s degree/University degree in Computer Science Engineering or equivalent experience
• Master’s degree in Computer Science Engineering preferred

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