Lead SQL Developer

Lead SQL DeveloperThis person will be responsible for maintaining the quality and direction of data solutions in support of our Finance team. The role requires knowledge of database development tools and services, with an emphasis on SSAS.Qualifications Experience Required: 7 - 10 Years Education Required: Bachelors DegreeMinimum seven (7+) years experience in a multi-disciplined IT environment with strong expertise in data analysis, data modeling, data governance and involvement in enterprise architecture Minimum of five (5+) years experience, hands-on, data profiling and performance tuning databases and data marts with Oracle and / or SQL Server Experience with performance improvement using Azure and/or on-premise Microsoft technologies Experience taking a leading role in architecting, designing and developing solutions exceeding business expectations Knowledge of interpreting business processes and requirements and translating them into logical and physical data models adhering to documented standards and best practices Excellent problem solving and communication skills with experience in interacting with business and technical teams at all levelsResponsibilitiesThis person will be ultimately responsible for performing the data analysis and profiling necessary to provide direction, standards, and implementation of data management solutions associated with data ingestion, transformation, integration, and analytics Engage in full stack Microsoft BI development activities to deploy usable and measurable projects meeting business needs leveraging tools such as SSIS, SSAS, stored procedures and Power BI Write complex Stored procedures to harmonize data sets for reporting Setup dimensional/tabular data models Setup and deploy row/object level security Develop and publish Power BI reports Provide input and implement solutions to drive the continuous improvement of the development and support teams Participate in data integration, business intelligence (BI), and enterprise information management programs by rationalizing data processing to support reuse