Data Architect - Spectrum Enterprise

Encourage company-wide excellence through active and consistent support of all efforts to simplify and enhance the client experience.Provide insight and technology recommendations by partnering with the IT and Business Intelligence (BI) team.Ensure data accuracy through the development and maintenance of data structures that draw information from multiple sources of data, such as corporate databases, corporate data warehouses and field operational data sources.Drive the data architecture development process by designing, delivering and documenting multi-platform architecture with a focus on architectural standards, growth, performance, flexibility, reliability, scalability and security.Identify architectural risks and mitigation plans through data generation and reporting with a minimum of downtime in the process.Work with vendors to develop metadata structures for two-way data communications that allow interchange between existing and new data sources.Improve ways of exchanging data with corporate or field clients by recommending and implementing new uses of network or web-based reports, forms or files.Exceed client expectations by generating new products for data licensing. Closely monitor the transfer from prototype to scheduled report to ensure project success.Manage the use of corporate data to create reports in Microsoft Excel, Crystal Reports and other reporting tools.Enhance reporting and data gathering abilities by identifying, evaluating and recommending desktop tools.Learn new desktop and external tools to enhance the team's ability to gather, process or report data and integrate these tools into existing structures. Quickly understand resolve issues by using business process knowledge to work with teams in Sales, Marketing, Finance and Operations.Support highly varied and high-velocity data processing and delivery through the design and development of extract, transform, load (ETL) replication schemes and query optimization techniques. Ensure projects are on time and meet quality standards by developing standards and methodologies for benchmarking, performance, evaluation, testing, data security and data privacy.Perform impact analysis, performance tuning and capacity planning for the data warehouse and infrastructure to ensure success for additional source systems and the integration of business rules and logic. Provide recommendations, technical direction and leadership for different technologies to improve the overall architecture.Required keys for success: