• Design and implement secure, resilient, and scalable warehouse architecture that meets current and future needs of the organization
• Design, develop and modify relational and multidimensional database structures, relationships, data flows and data interfaces within the data warehouse
• Understand thoroughly the architecture, data structures and fundamental design principles of the data warehouse
• Design and implement ETL procedures for intake of data from both internal and outside sources; as well as ensure data is verified and quality is checked
• Create written documentation and diagrams as required and/or requested including technical specifications, technical alternatives, structure charts, data flow diagrams
• Facilitate requirements gathering using expert listening skills and develop unique simple solutions to meet the immediate and long-term needs of business customers
• Consult with functional areas as requested to aid in the development of their test scenarios, test plans and test scripts and conduct unit test and debug code prior to delivery to client
• Monitor and support the data warehouse, including data integrations (Oracle, SQL Server, etc.), access management, load balancing, performance, and operational monitoring, meta and master data management, and advise team on improving the performance and reliability of the solution
• Experience with software document and version control
• Strong decision making, analytical, problem solving, and time management skills.
• Help and constructively mentor team members in their professional development.
• Perform any other related duties as required or assigned

Requirements

• 5+ years or more experience performing data warehouse architecture development and management
• Hands-on Experience with Power BI, Tableau, SportFire, TIBCO, QlikView, MicroStrategy, Information Builders, and other reporting and analytical tools
• Expertise with ETL tools like DataStage, Informatica, Pentaho, Talend, among others
• Sound knowledge in multiple databases e.g. SQL, PostgreSQL, MongoDB, Apache Cassandra, among others
• Working knowledge of SAS, Python and R code used in data processing and modeling tasks
• Extensive experience with Microsoft Azure and Amazon AWS computing platforms
• Strong experience with Hadoop, Impala, Pig, Hive, YARN, and other “big data” technologies

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