The Enterprise Data Warehouse Architect will be responsible for system design, implementation, and administration of all components that make up the Data Warehouse and Data marts infrastructure, applications and related tools. The candidate must demonstrate knowledge of data warehouse implementation process, from business requirements through logical modeling, physical database design, data sourcing and data transformation, data loading, developing the overall data warehouse architecture and physical implementation standards.
Serve as a technical expert to data warehouse project teams. Support for both logical and physical design work associated with data warehouses. Ability to collaborate with BI architects and conduct JAD sessions, driving requirements from our business customers. Analyze source system data structures and map them to target data warehouse schemas. Must have excellent skills in requirements analysis, data assessment, business process reengineering, and demonstrate expertise with data warehousing design concepts such as 3rd Normal Form and Dimensional modeling. Designing, creating physical database objects (tables, views, indexes) to support normalized and dimensional models. Work with development, application and other warehouse architects to provide an overall solution approach.
This is both a technical and leadership position. Will be required to present and communicate with executive level management. Must be comfortable communicating with and presenting to groups of experienced professionals on a regular basis. Will be the go-to technical leader.
- Architect the overall data warehouse design - conceptual, logical, and physical representations
- Work with the business analysts and/or functional users to perform detailed data analysis to develop the data model for the data warehouse and data marts.
- Design physical data models for multi-generation, full life cycle Data Warehouse.
- Create physical Database objects including fact tables, dimensions, staging, materialized views, indexes in accordance with logical data model provided by DW functional leads
- Partner with the Data Access, Data acquisition, Database Administration on design, administration, and support activities. Work closely with Business Analysts to understand and document business needs for decision support data.
- Identify and implement technologies for ongoing database scalability, monitoring and performance improvement
- Work with Data Warehouse team to stay up to date on procedures, products and technologies as they relate to technical progress, economic change and business needs.
- Work on ongoing documentation of database structure (ERD)
- Participate throughout the entire project life cycle to facilitate conformance to design methodology, overall data warehouse architectural compliance and infrastructure coordination and preparation. Resolve subsequent issues and make modifications to ensure ongoing correlation between data models and physical data base structure
- Responsible for preparation of database requirements throughout the data warehouse implementation
- Collaboration with various groups to identify and research data quality issues
Tool and Concepts
- Bare minimum of 5 years Database / Data Warehouse development / architecture experience and a total of 7 to 15 years in IT. Strong Analytical and dimensional modeling background is required.
- 8+ years of hands-on logical and physical database design
- * Provide technical leadership for establishing and maintaining solid Data Warehouse solutions.
- Be able to work with both non-technical and technical client community to accurately define data requirements
- Demonstrated ability to design and implement physical Star Schemas.
- Should have comprehensive knowledge of Oracle 8i/9i/10g and Teradata Database systems
- Must be a team player and be able to lead and mentor junior data warehouse developers.
- Good communication and presentation skills and must have the ability to work with people in various groups and departments both IT and business
- Informatica: ETL
- Business Objects, Cognos, Tableau, etc.
- Erwin: Data Modeling
- Kimball Methodology
- Abinitio's Metadata Repository
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