Data Warehouse Developer

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.

·         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