What are the responsibilities and job description for the Data modeler (Level 2) position at Steneral Consulting?
Role: Data modeler (Level 2)
Must Have Valid Linkedin
Location: Albany NY
Experience: 7 Years
Roles & Responsibilities
- Review business and technical artifacts and documentation to understand data and data modeling requirements.
- Participate in meetings and work with Business SMEs, Business Analysts and Technology teams to extract data requirements from functional, non-functional, and technical requirements.
- Perform analysis, design, development, and implementation, including data analysis, data validation, data access, data modeling, data transformation, data reporting solutions and documentation.
- Design, develop, deploy, verify, and maintain logical, conceptual, and physical data models based on requirements while adhering to agency standards, best practices, and conventions.
- Create and maintain technical documentation such as data dictionaries, data lineage, data mapping, data flow diagrams, and fit-gap analysis.
- Develop data modeling and data migration strategies, plans, schedules, tasks, and activities.
- Develop solutions adhering to data confidentiality, data integrity, data accessibility / availability, and data security standards and requirements.
- Act as a technical liaison working with technical teams to resolve problems and implement solutions.
- Monitor database to identify data quality issues and determine the resolution and revise the incorrect operational processes.
- Communicate and coordinate with members of the development team to work across multiple projects.
Mandatory Qualification
(PASS/FAIL)
- Level II- Between four (4) and seven (7) years of experience as a Developer
- Seven (7) years of hands-on experience in designing, developing, and implementing entity relational diagrams, conceptual, logical, and physical relational data models in third normalization form and canonical data models. This includes but not limited to creating new transactional tables, association tables, code tables, enterprise shared tables, domain specific tables, and transforming existing industry and/or enterprise data models to meet business requirements.
- Seven (7) years of demonstrated hands-on experience using data modeling software (e.g., Erwin Data Modeler) for designing models, forward engineering to generate data definition language (DDL), reverse engineering physical databases, and identifying / reconciling differences in multiple data models. This includes but not limited to creating subject areas, data models, naming standards, model templates, domains, macros, constraints, relationships, data modeling repository reports, or importing COBOL Copybook files into the data modeling software to expedite development.
Additional Qualifications:
- More than four (4) years or more of experience designing data models in third normalization form for data migration, data conversion, or consolidation projects in staging and OLTP environments, adhering to data modeling standards and best practices.
- More than four (4) years or more of demonstrated hands-on experience in designing data models based on legacy mainframe systems (e.g., Unisys) and transforming them to third normalization form in modern relational database management systems (e.g., Oracle).
- More than four (4) years or more of hands-on experience developing complex SQL queries, PL/SQL packages, stored procedures, functions, views, complex joins, indexes, triggers, external tables, roles, grants, permissions, DDL, and DML.
- More than four (4) years or more of experience in performance tuning SQL scripts, complex PL/SQL, complex joins, database objects (procedures, functions, triggers, packages, tables, views), and leveraging indexes for optimal database performance.
- More than four (4) years or more of demonstrated hands-on experience in creating comprehensive technical documentation such as data dictionaries, data lineage, data mapping, data flow diagrams, and fit-gap analysis.
- More than four (4) years or more of experience in transforming functional, non-functional, and technical requirements into data requirements.
- Four (4) years or more of experience in performing data analysis and metadata cataloging.
- Knowledge and experience in health and human services, especially in Integrated Eligibility System programs such as PA, TA, SNAP, HEAP, TANF, etc.
- Experience with implementing data modeling solutions for medium to large scale, high volume OLTP systems especially for Case Management systems, Enrollment and Eligibility systems, Financial Management systems, Child Support systems, Appointment / Scheduling systems, or similar Party Data Model like systems.
- Knowledge and experience in applying data management concepts such as data architecture, data quality, metadata management, data integrity, data integration, data governance, data security and master data management.
