Architect (ATC)

Information Architect data dimensional modeling JD

The data modeler designs, implements, and documents data architecture and data modeling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, machine learning, data science, and other business interests.

The successful candidate will


Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store ODS, data marts, and data lakes on target platforms SQL NoSQL.

Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively.

Responsibilities

Implement business and IT data requirements through new data strategies and designs across all data platforms relational, dimensional, and NoSQL and data tools reporting, visualization, analytics, and machine learning.

Work with business and application solution teams to implement data strategies, build data flows, and develop conceptual logical physical data models

Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.

Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.

Hands on modeling, design, configuration, installation, performance tuning, and sandbox POC.

Work proactively and independently to address project requirements and articulate issues challenges to reduce project delivery risks.

Skills

Bachelors or masters degree in computerdata science technical or related experience.
5 years of hands on relational, dimensional, and or analytic experience using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols.

Experience with data warehouse, data lake, and enterprise big data platforms in multi data center contexts required.

Good knowledge of metadata management, data modeling, and related tools required.

Experience in team management, communication, and presentation.