Overview
Skills
Job Details
Technical Requirements: Cloud Platform: Azure
Additional Tools: Snowflake, Kafka - Technical Stack: Azure, AKS, Spring Boot
Critical Skill: SQL expertise Basic financial services experience preferred - Data modeling skills helpful - API design and optimization experience
Role Details: 20% business interaction - 40% architecture/design work - 40% coding and developer guidance
Located at Wabash office (3 days on-site required) - Supporting Asset Servicing division
Job Description
This person will be responsible for visualizing and designing our data management framework. This framework describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data in the consumer view. He/she will also provide a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture.
Qualifications (must haves):
A foundation in systems development (API and data-oriented systems)
Data design
Data and Application Architectures for cloud-based systems
Data model design and pipelines for real-time Data Processing, streaming, networking, and security
Established and emerging cloud technologies
Communication and political savvy
Problem solving / analytical thinking and skills
Teamwork and collaboration
Tasks & Responsibilities:
Apply data management and architecture expertise in developing solution architecture and advanced analytics solution design, including reporting technology; Articulate tradeoffs, strengths, and weaknesses of various architectures and their components to determine the best design given use cases and constraints
System design and tuning for cloud-based data or API applications
Identify internal and external data sources for potential integration into platform; Lead data migration and integration projects
Create appropriate standards and processes to ensure quality and consistency of data in the platform
Outline best practices and establish standards for data strategy, data lifecycle, data ownership, data definition, and data classification,
Collaborate with stakeholders and advanced analytics business partners to understand business needs and to identify and define advanced analytics solutions