Required Education:
BS/BA degree in Computer Science, Information Systems, or related field
Required Skills:
Experience using Qlik or related Business Intelligence technologies such as WebFocus, Tableau, PowerBI
Deep understanding of high-performant data concepts such as file stores, wide column databases, key-value pairs, etc.
Excellent oral and written communication
Excellent problem-solving skills
Highly analytical with the ability to work independently
Expertise with Java, API, Angular, React
Building Agentic Framework using MCP layers and LLMs
Logical designing and Analytical skills based on product and platform requirement.
Desired Skills:
Experience working with open source software
Experience working with extremely large data sets
Experience integrating new and emerging technologies into existing environments
Provide oversight and guidance to Data Engineering development team
Role:
The Software Engineer role is responsible for working on developing data engineering solutions, approaches for ingestion, transformation and storage. In addition, you ll work within the Fraud Data Engineering team to grow their knowledge and expertise. You will get the chance to work with extremely large data sets and be on the cutting edge of transforming the way we captures, processes, stores and visualizes transactional data.
Responsibilities:
Explore and develop Framework to support Agentic products
Develop both internal and external dashboards using Qlik
Work closely with team members from to identify functional and system requirements
Work with team in resolving any issues that arise with dashboards, tasks, user access.
Install the Qlik Sense Application expand clusters, add new clusters rare but important.
Configure the application
Add/Remove/Maintain Data sources
Manage dashboard deployments
Maintain Security Rules Add/Remove/Modify as needed
Periodic evaluation of clusters with team management
Design, develop and implement DataMart's with quality and integrity at the top of mind to support our products
Create documentation to support knowledge sharing; including flowcharts and diagrams
Provide oversight and guidance to our Data Engineering development team
Read and interpret conceptual, logical, and physical models
Understand data modeling concepts and their application: entities and tables, relations and constraints, attribute data types and column data types
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