Data Modeler

Sligo Software Solutions

New York, NY

Expired: 15 days ago Applications are no longer accepted.

Full-Time

Job Description

Company Info

Job Description

Job Reference # COB000001017

Job Title: Developer
Location: Remote

Duration: 6 Months

The Data Modeler is primarily responsible for the design, implementation, and maintenance of data models to support the needs of data warehouses and data marts. The position is responsible for recommending and adopting best practices to ensure high data quality standards, repeatability and scalability of data models are designed, and maintained and data redundancy is reduced.

General tasks and responsibilities will include:

Understand and translate business needs into data models to satisfy enterprise analytics & reporting needs
Work with the EIM team to design and implement data models, build data flows and develop conceptual, logical and physical data models.
Development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lake. Optimize and update logical and physical data models to support new and existing projects.
Maintain conceptual, logical and physical data models along with corresponding metadata.
Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
Recommend opportunities for reuse of data models in new environments.
Perform reverse engineering of physical data models from databases and SQL scripts.
Evaluate data models and physical databases for variances and discrepancies.
Validate business data objects for accuracy and completeness.
Analyze data-related system integration challenges and propose appropriate solutions.
Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.

Minimum Qualifications:

A Baccalaureate Degree from an accredited college or university with a major in Computer Science, Systems Engineering, applied Mathematics, Business Administration, Economics/Statistics, Telecommunications, Data Communications, or a related field of study; and
Five (5) years of progressive, responsible experience in the field of data processing, computer systems and applications.
Operations Specialty requires supervisory experience (5 years).
Network Services requires a telecommunications background and experience.
Broad knowledge and expertise in the characteristics of computers, peripheral devices, communications systems and hardware capabilities, programming languages, E.D.P. applications, systems analysis methodology, data management and retrieval techniques; or
A satisfactory equivalent combination of training, education and experience.

Department Preferences:

Proficiency with some leading data profiling tools (such as SQL, BI tools, etc).
Experience with Enterprise Data Warehouse initiatives including Data Model development, Semantic/Data Access Layer Development, Reporting and Dashboard Creation; developing solutions for shared data usage.
Experience with a Data Modeling tools (such as Erwin) and in developing processes to manage data model development, principles, and standards.
Experience with a Clinical industry focused data model preferred.
Exposure to and understanding of Analytical Architectures.
Consulting and Facilitation Skills.
Advanced decision making and problem-solving skills.
Business acumen, knowledge, and professionalism.
Strong analytical, problem solving, and work management skills.
Customer-focused ability to communicate across all levels of the organization.
Proactive Leadership style; self-starter and strong attention to detail.
PC and/or OS operating systems
Microsoft Office (Word, Excel, Access, PowerPoint, MS Project, Visio, SharePoint)
SQL, BI Tools
EDW (Snowflake)
Data Modeling Tool (ex: Erwin)
5+ years of experience working with healthcare data and revenue cycle data models.
7+ years of experience in designing scalable enterprise data models
7+ years of work experience in design and implementation of data models for complex data warehouse initiatives.