Data modeller

About the job Data modeller

Job Description-Data Modeller

The data modeler designs, implements, and documents data architecture and data modeling solutions,
which include the use of dimensional and relational. These solutions support enterprise information
management, business intelligence especially for Utilities Asset Management domain.
The successful candidate will:
1. Be responsible for the development of the conceptual, logical, and physical data models as part
of the Enterprise Data Warehouse of Horizon Power with special emphasis to Asset Data
Warehousing, the implementation of RDBMS, operational data store (ODS), data marts, and
data lakes on target platforms
2. Oversee and govern the expansion of data architecture and the optimization of data query
performance via best practices. The candidate must be able to work independently and
collaboratively.
3. Be very effective in client engagement both in onsite physical as well as offsite digital modes
4. Work in cross-functional teams with Engineering and Industrial to create an effective output for
the customer

Responsibilities
 Implement business and IT data requirements through new data strategies and designs
across all data platforms (relational, dimensional) and data tools (reporting, visualization,
analytics).
 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 knowledge
 Work proactively and independently to address project requirements and articulate
issues/challenges to reduce project delivery risks.

Skills

 Bachelor’s or master’s degree in computer/data science technical or related experience.
 5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS,
dimensional, 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 (Erwin or ER
Studio or others) required.
 Experience working in cross-functional teams, manage teams, communication - internal as
well as external, and presentation.
 Would be an advantage to have asset data exposure (non-mandatory)