Enterprise Data Modeler/ Architect

Job Title: Enterprise Data Modeler/ ArchitectLocation: Hy-bride ( Mentor, OH)Job Type: Contract to Hire

Job Description

Position Summary

The Enterprise Data Modeler/Architect is responsible for architecting, designing and developing robust and scalable

data models and deploying data structures for Client enterprise cloud data warehouse, data lake, data hub

and other specialized data stores to support reporting, analytic and data science use cases. Works closely with

business stakeholders, data engineers, and analysts to understand data and analytics needs and translate them

into efficient and effective data models.

The Enterprise Data Architect \ Data Modeler leverages knowledge of data modeling best practices along with cross

industry data expertise and data modeling tool expertise. Demonstrates mastery of skills and knowledge and is a

mentor, strategist, thought leader, evangelist, champion, plans and leads data modeling activities.

Responsibilities

• 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,

reporting, business intelligence, machine learning, data science, and other business use cases.

• Designs and maintain conceptual, logical and physical data models for the enterprise data warehouse (EDW),

data lake and other data stores, adhering to best practices and industry standards.

• Collaborate with business stakeholders to understand data requirements and translate them into clear and

concise data models.

• Oversee and govern the expansion of existing data repositories and data architecture, and the standardization

and optimization of data designs across all data platforms (relational, dimensional, and NoSQL) and data tools

(reporting, visualization, analytics, and machine learning).

• Define and govern data modeling and design standards, tools, best practices, and related development for

enterprise data models.

• Conduct assessment and profiling of potential data sources to understand source data structure and content to

inform design of target data models.

• Develop and maintain data dictionaries, data glossary, and contribute to develop data catalog metadata models

and content.

• Develops, maintains and communicate standards and guidelines for data models and schema objects (e.g.,

naming standards). Defines and implements administration and control activities related to data warehouse

planning and development.

• Work with data engineers to ensure data models are compatible with data extraction, transformation, and

loading (ETL/data pipeline) processes.

• Document data models thoroughly, including entity relationships, data definitions, and transformations.
• Research and apply innovations in technology and best practices related to cloud data warehousing, data lakes

and data modeling.

• Identify and recommend opportunities to optimize data models for performance and scalability.
• Leads the selection and development of data modelling and design methodology, best practices, tools, and

techniques.

• Support data analysts and other data users in understanding and utilizing the data warehouse and data lake.
• Contribute to the development of training and support program.

Specific Skills and/or Business Competencie

• Expert experience with data modeling tools such as Erwin, Embarcadero ER Studio, or IBM InfoSphere

Data Architect.

• Created and maintained database objects, tables, views, indexes, synonyms, partitions, triggers, stored

procedures in the data model (using data model tool)

• Strong expertise with version control methodology for data models.
• Strong SQL query skills, SQL programming skills, and development of DDL scripts to create and maintain

database schemas.

• Strong knowledge of dimensional data modeling concepts. Expert knowledge of Kimball and Inmon

methodologies.

• Experience with BI, reporting and ETL tools is a plus.
• Data profiling and data validation using SQL queries and back-end testing. Use of data profiling and data quality tools to gain understanding of source data content and assess degree of data quality. 8. Ability to conduct and lead independently users’ and SMEs’ requirements interviews, and JAR/JAD sessions to elicit data model requirements, determine data definitions, and business rules. 9. Experience with Snowflake, Oracle, MS SQL Server, Azure Data Lake Storage, Databricks, Informatica IDMC or PowerCenter, Tableau and Cognos preferred. 10. Experience with Agile SDLCs and DevOps

Regards

Mark Sr.IT Recruiter Mark_US@falconsmartit.com