Job Description :
Job Requirements:
Job Summary/Purpose
This IT position is a key role in the Enterprise Analytics team supporting the Enterprise Data Lake ecosystem.
The Data Modeler – Enterprise Analytics plays an integral role in building a holistic view and roadmap of the company’s technology strategy, processes, and information technology roadmap. The data modeler partners with both business and technology groups to ensure that the proposed technical solutions align with the company’s overall mission, vision, strategy, goals and objectives. This role, Data Modeler – Enterprise Analytics, will be responsible for the data modeling and metadata management portion of the Enterprise Data Lake ecosystem. As such, this role will be expected to develop and maintain Entergy’s Enterprise Data Lake data and metadata catalogues and mappings, plus design, access, usage and stewardship. Also included is the development or use of process models, interface designs, and development of internal and external checks and controls to ensure proper governance, security and quality of data assets.
This position requires strong technical and communication skills, as well as proven experience in data management, information management, big data strategy and planning, information modeling and delivery, agile implementation, business collaboration, program management and project management, and the utility industry in general. This role will report directly to the IT Service Pod Manager – Enterprise Analytics, plus there is a matrixed relationship to the Enterprise Analytics team. This role will directly interact with other roles such as: Solution Architect, Data Architect, Data Wrangler, and Data Scientist.
Definition refinement, ownership and representation of the Enterprise Data Lake Reference Architecture, including:
Data Supply & Integration Architecture, Tools and Platforms
Analytics Delivery Architecture, Tools and Platforms
Representation and alignment of the Enterprise Data Lake Reference Architecture to enterprise and local analytics architecture teams
Manage and coordinate new information demand that impacts the Enterprise Data Lake Reference Architecture
Capture business capability requirements, functional requirements, and expected service levels from business units
Establish design guidelines data integration, performance, reliability, operating, and security designs. Support business units in the creation and implementation of project use cases
Maintain an understanding of data and metadata needs for business units
Job Duties/Responsibilities:
1General: Working under the direction of the IT Service Pod Manager for Enterprise Analytics; translate project goals into usable data models to guide project solution development and achieve consistency of information assets across the entire application portfolio. Simply stated leads the data modeling activity for the Enterprise Data Lake ecosystem, across multiple content types (structured data, semi-structured data and unstructured data) inclusive of Data Management, Information Management, and Analytics solutions. Participates in the development of Enterprise Analytics solution strategy and the identification and design of IT architectures to support emerging business strategic intent (e.g., Big Data management and analytics
2Architecture: Establishes data modeling standards and best practices. Designs and implements the Enterprise Data Lake data models, working closely with the IT Enterprise Architecture team plus other Data Lake and Analytics teams. Translate the Enterprise Data Lake Reference Architecture into an operational ecosystem. Works closely with the Data Architect to design and implement Enterprise Data Lake solutions. Responsible for the overall design and build of the Enterprise Data Lake data model domain inclusive of Data Management, Information Management, and Analytics solutions.
3Data Management Technologies: Responsibilities also include the creation or use of enterprise data management processes, models and technologies; data interface designs, and development of internal and external checks and controls to ensure proper governance and quality of data assets, inclusive of enterprise methods and standards. As needed, lead or participate in POC investigative and research projects.
4Analytics Technologies: Responsibilities also include the creation or use of enterprise analytical data models and technologies; analytical data architectures, inclusive of enterprise methods and standards. As needed, lead or participate in POC investigative and research projects.
5Day-To-Day Duties: Wear many hats and provide data and metadata expertise across the entire Enterprise Data Lake ecosystem
6Roadmap: Participate in data strategy and road map exercises, data architecture definition, business intelligence / data warehouse product selection, design and implementation
7SDLC: Work through all stages of a data solution life cycle: analyze/profile data, create conceptual, logical & physical data model designs, assist with ETL design, reporting and analytics solutions
8Matrix Collaboration: Works collaboratively with all IT and business teams; works collaboratively with the Enterprise Analytics team, Enterprise Architecture team, plus other business analytics teams. Leads the oversight of other data modelers, as needed. Works closely with the Data Architect to design and implement Enterprise Data Lake solutions. Works closely with the Database Management Admin (DBA) team to design and implement Enterprise Data Lake solutions. Works closely with the Data Governance team to help manage and support Enterprise Data Lake data management solutions. Works closely with all teams to support and maintain metadata libraries and catalogs.
9Consulting: Provide primary advisory and consulting services for technical aspects of Enterprise Analytics solutions and applications (Entergy’s Subject Matter Expert on the Enterprise Data Lake technology stack and associated data architectures Be a thought-leader at Entergy for solving data quality/availability issues and work with the data scientists and citizen data scientists throughout Entergy various business units. Participates in the development of Enterprise Analytics solution strategy.
10Communication: Communicate and collaborate with all Enterprise Analytics stakeholders.
Minimum Requirements:
Minimum education required of the position:
Bachelor''s degree in related field such as business, engineering or IT (or equivalent work experience MBA or graduate degree in IT or engineering or relevant discipline preferred.
Minimum experience required of the position
Minimum of 8+ years in Information Technology experience required. Experience in large scale or enterprise projects, including data architecture and/or analytics leadership experience (e.g., data architect, analytics architect, solution architect level experience Experience with electric utility distribution grid technologies and customer systems preferred.
Minimum knowledge, skills and abilities required of the position:
1. Strong interpersonal, collaboration, leadership, and analytical skills.
2. Demonstrated strong work ethic and exceptional levels of accountability, self-drive, and business judgment
3. Excellent oral and written communications skills.
4. Strong presentation development and delivery skills.
5. Experience with information technology implementation and/or systems development and implementation life cycles from both a technical (IT) and functional business data perspective.
6. Working knowledge of enterprise application and infrastructure platforms, development methodologies and industry best practices.
7. In-depth experience designing and implementing information solutions; previous Smart Grid or Big Data experience a plus.
8. Knowledgeable in the design and construction of information architectures especially collaborative and analytical systems.
9. Data/information modeling experience at the enterprise level.
10. Understanding of common information architecture frameworks (such as Zachman and TOGAF
11. Understanding of differences of conceptual, logical, physical data modeling.
12. Understanding of taxonomies and ontologies, as well as the methods of managing structured data, semi-structured data, and unstructured data.
13. Ability to effectively adapt to rapidly changing technology and apply it to business needs.
14. Ability to establish and maintain a high level of customer trust and confidence.
15. Strong analytical and conceptual skills; ability to create original concepts/theories for a variety of stakeholders.
16. Ability to analyze project, program and portfolio needs, as well as determine resources needed to meet objectives and solve problems that involve remote and elusive symptoms, often spanning multiple environments in a business area.
17. Working knowledge of project planning and management, including scope, time and resource management.
18. Experience creating information policy to support effective design of information systems and use of information across the enterprise.
19. Experience with various information modeling techniques (such as data flow diagrams, entity-relationship diagrams or create/read/update/delete matrices
20. Familiarity with business intelligence and data warehousing data and application architectures and technologies.
21. High-level understanding of relational database management systems and other data structures (e.g., Hadoop
22. Familiarity with program and project management including governance, compliance, roles and responsibilities, methodologies, processes and procedures.
23. Familiarity or experience with budgeting, analysis, forecasting, and reporting.
24. Familiarity or experience with engineering and/or operations of IT lifecycle, digital communications, information assurance, and cyber security.
25. Knowledge and understanding of the organization''s business operations and industry.