Senior Data Architect

Senior Data Architect

Influence projects/initiatives and drive decisions related to data including data quality, data architecture and data management best practices. Provide expert data modeling and data validation services that produce flexible, extensible data structure design solutions that support effective business decisions. Map entities to use cases and business requirements and assist in the development of data services. Create and manage an array of data design deliverables including data models, data diagrams, data flows and corresponding data dictionary documentation. Develop standards for database design and implementation of various strategic data architecture initiatives around master data management, data quality, data management policies/standards, data governance and metadata management. Serve as an advocate for the data architecture team and data management discipline, policies and standards across the enterprise. Assist in determining the effectiveness of existing technologies and processes in relation to the data architecture, create necessary implementation/migration plans, and recommend new solutions as required. Identify opportunities for sharing and utilizing data across boundaries, thus extracting maximum benefit from the data resource. Lead associates in data utilization; understanding and interpreting raw data and converting it into information. Support analysts in requirements development, research and verification.

Academic/Experience/Competency: Bachelors Degree, or Masters degree in Computer Science, or applicable field of study. Proven background of designing and implementing architectural solutions which solve strategic and tactical business needs. Strong technical understanding of data modeling, design and architecture principles and techniques across master data, transaction data and derived/analytic data. Deep knowledge of best practices through relevant experience across data-related disciplines and technologies, particularly for enterprise-wide data architectures, data management, data governance and data warehousing. Highly competent with relational database design and structured query language (SQL). Highly competent with data modeling using industry leading tools like ERWIN or ERStudio. Strong familiarity with data management tools, including enterprise repository tools, data modeling tools, data quality tools, data mapping tools, and data profiling tools. BI and Data Warehouse technologies (e.g., Business Objects, SPSS, OBIEE, Informatica, TIBCO, MicroStrategy, SAS, Clarabridge). Strong aptitude to learn business processes/products and the role of data within the business domain. Strong conceptual knowledge of roles and responsibilities within BI and Data Warehousing (DA, ETL, BI, DBA, SE, QA, and PM). Working knowledge of SDLCs (RUP, Waterfall, and Agile). Demonstrated ability to balance architectural theory with practical solutions. Ability to adapt quickly in a rapidly changing dynamic environment. Ability to manage a large workload covering multiple projects and business disciplines. Excellent organizational and negotiating skills. Highly motivated, self-directed, results oriented problem solver.

Business Experience: 5-8 years of experience in data architecture principles, methods, techniques and technologies. Daily Tasks Performed: Lead key business critical projects in the capacity of a Data Architect and Advisor. Define Data Architecture standards, best practices and participate in governance activities. Lead key data architecture & data management initiatives. Review business requirements and technical design documents to develop effective data and database solutions. Create, maintain and define Conceptual, Logical, and Physical Data Models for various Honda manufacturing projects using relational theory and dimensional modelling, align them to Enterprise Architecture. Provide insight into logical business data requirement to work with DBAs to support physical data model considerations. Define, maintain and adhere to enterprise modelling standards. Develop ETL specification and document data migration mappings and transformations for data warehouse loading.

Wants: Expert level understanding of Modern Data Warehouse Concepts. 3-4 Years of experience with Big Data platforms. Understanding of advance analytics needs such as Predictive/Cognitive Analytics concepts. Exposure to cloud based data & analytics solutions.