Data Manager

Please Note - NP should be 0-15 days.

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 computer/data 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-datacenter contexts required.

-Good knowledge of metadata management, data modeling, and related tools

(Erwin or ER Studio or others) required.

- Experience in team management, communication, and presentation.