Data Architect (Azure, AKS, Spring Boot, SQL - Asset Servicing) - W2 (NO C2C,1099) - Chicago, IL (3 days per week) - Posted by Tauqeer

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 6 Month(s)
No Travel Required

Skills

Azure
API
SQL
Data Management
AKS
Spring Boot
Data Migration
Financial Services
Data Modeling
Kafka
Snowflake

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

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