Electricenergyonline
Data Architect, Data Modeling & Integration Design Focus TECO Energy Location: F
Electricenergyonline, Tampa, Florida, us, 33646
FOCUS AREAS
Advanced Data Modeling and Database Design
Cloud Data Platform Expertise
Data Governance, Security, and Compliance
ETL/ELT and Data Integration Design
Data Virtualization and Data Mesh Design
Build Data Architecture
POSITION CONCEPT The Data Architects responsible for the "back end" components of the organizations Data Analytics environment from standards, architecture, and design perspectives. Overall responsibility for the implementation and support of the data movement and engineering processes required to populate the organizations custom-built analytic data structures (e.g., staging areas, data warehouse and data marts) as well as the design of these structures. Responsible for the strategy and design related to the federation of custom-built data architecture with vendor provided solutions. Provides technical oversight and assures the quality of the work done by data analysts and data engineers and developers. Serve as a subject matter expert with significant, recent hands‑on experience with state‑of‑the‑art data integration and cleansing tools available in the SAP and Azure platforms etc. Responsible for assuring that data integration and cleansing tool suites are effectively deployed and applications are developed based on industry and vendor‑specified best practices. Responsibility for ensuring that the organizations analytic data architecture effectively enables needed applications and develops standards in the areas of data modeling, metadata management, data integration and master data management.
PRIMARY DUTIES AND RESPONSIBILITIES
Define and evolve the data architecture in alignment with enterprise standards to support diverse use cases such as reporting, OLAP, dashboards, data mining, and statistical analysis. Ensure the architecture meets operational requirements including scalability, security, reliability, and flexibility. Determine the appropriate deployment environment, whether cloud-based or on-premises. (25%)
Responsible for establishing best practices for source data analysis, ETL design and documentation, data federation across platforms (e.g., AMI, Empower, custom analytics), business rule placement (with the Information Architect), ETL testing and release management (with the Change Coordinator), database-level security (with DBAs), and data masking, anonymization, and tokenization. (15%)
Translates user requirements into data models and supporting applications by guiding data analysts in source analysis, advising ETL developers, and designing logical and physical analytic data structures. Responsibilities include deploying metadata tools to document data sources, analytic structures, semantic layers, and BI applications; implementing security for data integration and cleansing tools; collaborating on support environments and release management best practices; overseeing the operational environment; and working with DBAs and operations teams to monitor and optimize ETL and data structure performance. (15%)
Accountable for the quality of data model and ETL application deliverables and so is responsible for establishing and managing QA related functions including Testing (unit, system, stress, etc.) and Peer reviews (e.g., reviews of data models, ETL application design, etc.) (15%)
Provides technical oversight of the activities of ETL developers and data analysts and provide coaching and mentoring regarding technical skills and competencies. (15%)
Serves as a technical subject matter expert (SME) to provide consultation. (15%)
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Advanced Data Modeling and Database Design
Cloud Data Platform Expertise
Data Governance, Security, and Compliance
ETL/ELT and Data Integration Design
Data Virtualization and Data Mesh Design
Build Data Architecture
POSITION CONCEPT The Data Architects responsible for the "back end" components of the organizations Data Analytics environment from standards, architecture, and design perspectives. Overall responsibility for the implementation and support of the data movement and engineering processes required to populate the organizations custom-built analytic data structures (e.g., staging areas, data warehouse and data marts) as well as the design of these structures. Responsible for the strategy and design related to the federation of custom-built data architecture with vendor provided solutions. Provides technical oversight and assures the quality of the work done by data analysts and data engineers and developers. Serve as a subject matter expert with significant, recent hands‑on experience with state‑of‑the‑art data integration and cleansing tools available in the SAP and Azure platforms etc. Responsible for assuring that data integration and cleansing tool suites are effectively deployed and applications are developed based on industry and vendor‑specified best practices. Responsibility for ensuring that the organizations analytic data architecture effectively enables needed applications and develops standards in the areas of data modeling, metadata management, data integration and master data management.
PRIMARY DUTIES AND RESPONSIBILITIES
Define and evolve the data architecture in alignment with enterprise standards to support diverse use cases such as reporting, OLAP, dashboards, data mining, and statistical analysis. Ensure the architecture meets operational requirements including scalability, security, reliability, and flexibility. Determine the appropriate deployment environment, whether cloud-based or on-premises. (25%)
Responsible for establishing best practices for source data analysis, ETL design and documentation, data federation across platforms (e.g., AMI, Empower, custom analytics), business rule placement (with the Information Architect), ETL testing and release management (with the Change Coordinator), database-level security (with DBAs), and data masking, anonymization, and tokenization. (15%)
Translates user requirements into data models and supporting applications by guiding data analysts in source analysis, advising ETL developers, and designing logical and physical analytic data structures. Responsibilities include deploying metadata tools to document data sources, analytic structures, semantic layers, and BI applications; implementing security for data integration and cleansing tools; collaborating on support environments and release management best practices; overseeing the operational environment; and working with DBAs and operations teams to monitor and optimize ETL and data structure performance. (15%)
Accountable for the quality of data model and ETL application deliverables and so is responsible for establishing and managing QA related functions including Testing (unit, system, stress, etc.) and Peer reviews (e.g., reviews of data models, ETL application design, etc.) (15%)
Provides technical oversight of the activities of ETL developers and data analysts and provide coaching and mentoring regarding technical skills and competencies. (15%)
Serves as a technical subject matter expert (SME) to provide consultation. (15%)
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