Data Architect

vzc Головна Вакансії компанії Intellias Data Architect

Project Overview:

Our US based client is a third-party- administrator (TPA) in Utah that creates and administers group health plans. Its goal is to help small and medium-sized businesses offer affordable group health benefits to their employees. They offer group health plans that are made simple for employees and employers alike. Technology-wise: our client works on various products for enhancing communication and processing of medical claims, invoices etc.

Рекрутерка

Ольга Гук

Responsibilities:

Work with the customer, users, technical architects, and application designers to define the data requirements and structure for the application;
Model and design the application data structure, storage, and integration;
Lead the database analysis, design, and build effort;
Work with the application architects and designers to design the integration solution;
Ensure that the database designs fulfill the requirements, including data volume, frequency needs, and long-term data growth;
Build reports and dashboard in PowerBi where the data comes from the EDW.

Requirements:

Experience with building data platform on cloud (AWS);
Expert in SQL and no-sql models;
Power BI is a must;
Experience with AWS and AWS hosted data warehouses;
Strong technical understanding of data modeling, design and architecture principles and techniques across master data, transaction data and derived/analytic data;
Understanding of advance analytics needs such as Predictive/Cognitive Analytics concepts;
Proven background of designing and implementing architectural solutions which solve strategic and tactical business needs;
Deep knowledge of best practices through relevant experience across data-related disciplines and technologies, particularly for enterprise-wide data architectures, data management,data governance and data warehousing ;
Highly competent with data modeling;
Strong Data Warehousing and Business Intelligence skills or including: Handling ELT and scalability issues for enterprise level data warehouse;
Creating ETLs/ELTs to handle data from various data sources and various formats;
Strong troubleshooting and problem solving skills in large data environment.