
Responsible for planning, connecting, designing, scheduling, and deploying data warehouse systems. Develops, monitors, and maintains ETL processes, reporting applications, and data warehouse design. |
Role and Responsibility |
· Plan, create, coordinate, and deploy data warehouses. · Design end user interface. · Create best practices for data loading and extraction. · Develop data architecture, data modeling, and ETFL mapping solutions within structured data warehouse environment. · Develop reporting applications and data warehouse consistency. · Facilitate requirements gathering using expert listening skills and develop unique simple solutions to meet the immediate and long-term needs of business customers. · Supervise design throughout implementation process. · Design and build cubes while performing custom scripts. · Develop and implement ETL routines according to the DWH design and architecture. · Support the development and validation required through the lifecycle of the DWH and Business Intelligence systems, maintain user connectivity, and provide adequate security for data warehouse. · Monitor the DWH and BI systems performance and integrity provide corrective and preventative maintenance as required. · Manage multiple projects at once. |
DESIRABLE SKILL SET |
· Experience with technologies such as MySQL, MongoDB, SQL Server 2008, as well as with newer ones like SSIS and stored procedures · Exceptional experience developing codes, testing for quality assurance, administering RDBMS, and monitoring of database · High proficiency in dimensional modeling techniques and their applications · Strong analytical, consultative, and communication skills; as well as the ability to make good judgment and work with both technical and business personnel · Several years working experience with Tableau, MicroStrategy, Information Builders, and other reporting and analytical tools · Working knowledge of SAS and R code used in data processing and modeling tasks · Strong experience with Hadoop, Impala, Pig, Hive, YARN, and other “big data” technologies such as AWS Redshift or Google Big Data
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