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- The client has several new initiatives underway and have a need to insure that the applications are adhering to data standards and are fully integrated between these systems and any gaps are identified.
- The client is seeking a seasoned Data Architect who will be reviewing, designing, developing, and implementing data models for enterprise-level applications and systems.
- The candidate must have experience in data warehouse models in addition to OLTP models, these models shall be architected at the following layers: conceptual, logical, physical, subject area, and application.
- Under general supervision, the Data Architect shall provide strategic level technical leadership for the data architecture and must be able to perform hands on analysis and modeling.
- He or she must clearly understand business objectives, translate them into data models and communicate these data models to business and technical stakeholders verbally, in writing, and electronically.
- He or she needs to be able to understand the different standards in the Education domain CEDS, ED-FI, SIF, models and provide guidance to technical staff, project managers and insure vendors adhere to the standards.
- Through the development of reliable and stable data models, master data management, metadata management, and data quality assurance initiatives, the Data Architect will oversee the technical design of the Enterprise Data Architecture.
- He or she will define data modeling methodologies, standards, and tools. In collaboration with other stakeholders, the Data Architect shall define data interface and messaging standards for the client systems to integrate systems internally and externally.
- Strategy & Planning
- Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, department managers, clients, and other key stakeholders
- Assess and determine governance, stewardship, and frameworks for managing data across the organization
- Oversight of design implementation, providing assurance that key requirements are preserved and those gaps are understood and communicated to stakeholders as appropriate.
- Ensures design governance across projects, applications and infrastructure.
- Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap
- Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity
- Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement
- Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks.
- Ensure that data strategies and architectures are in regulatory compliance
- Ensure the success of enterprise-level application rollouts (e.g., P20 data warehouse, Common Core standards, etc.) from the data architecture, standards, and quality perspective
- Operational Management
- Develop and promote data management methodologies and standards
- Hands on?responsible for the implementation of the conceptual, logical and physical models using EOE tools.
- Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality
- Select and implement the appropriate methodologies, standards, tools, software, applications, and systems to support data technology goals
- Address data-related problems in regards to systems integration, compatibility, and multiple-platform integration
- Act as a leader and advocate of data management, including coaching, training, and career development to staff
- Develop and implement key components as needed to create testing criteria in order to guarantee the fidelity and performance of data architecture
- Document the data architecture and environment in order to maintain a current and accurate view of the larger data picture. Identify and develop opportunities for data reuse, migration, or retirement
- Develop integration process data flows and data mapping analyses
Education and Experience Level:
- Sensitivity to interpersonal, organizational and political challenges, and an understanding of how to navigate them effectively.
- Hands-on knowledge of enterprise repository tools, data modeling tools, data mapping, tools, data profiling tools, and data and information system life cycle methodologies
- 7 or more years of data or information architectureexperience, preferably in an education environment
- 5 years of work experience with data architecting, large-scale data modeling, and business requirements gathering/analysis
- Direct experience in implementing enterprise data management processes, procedures, and decision support
- Strong understanding of relational, dimensional and object-oriented data structures, theories, principles, and practices
- Experience with dimensional modeling and architectureexperience implementing proper data structures for analytical reporting from an enterprise data warehouse.
- Excellent client/user interaction skills to determine requirements and the ability to present ideas to various audiences in user-friendly language
- Proven project management experience
- Strong familiarity with master data and metadata management and associated processes
- Bachelor?s Degree in Computer Science, Information Systems or Business Administration
- Experience with Oracle ODI, Oracle Profiling and data quality
- Understanding of Education Data standards
- Good knowledge of applicable data privacy practices and laws (FERPA)
- Technical leadership and mentoring skills.
- Experience with Oracle Exadata a plus.