Required qualifications will include (but are not limited to):

• Graduate degree in Computer Science, Statistics, or a related field.

• Experience working in Business Intelligence and Data Warehousing using Extract, Transform, and Load (ETL) techniques.

• Proficiency in Structured Query Language (SQL) Server technologies, including QL Server Reporting Services (SSRS) platforms.

• Mastery of data management tools, including R or Python and associated libraries, e.g., dplyr, pandas, and numpy.

• Ability to support cloud-based applications, e.g., GitHub, Amazon Web Services (AWS), Microsoft Azure, using parallel computing environments, including Hadoop and MapReduce.

• Fluency in SPSS or SAS.

• Solid understanding of standard concepts, practices, and procedures within a programming environment.

• Ability to work under pressure.

• Excellent organizational skills.

• Willingness to work in a collaborative environment.

• Superb communication and writing skills.

Position responsibilities are:

• Build project databases and develop SQL Cube to automate existing projects.

• Perform regular ETL, data warehousing, and SSRS for reporting.

• Leverage SQL for special client projects as requested, e.g., client databases, custom reporting, and ad hoc applications.

• Provide Database Administrator (DBA) support including file management, archiving, and script execution supporting research managers.

• Perform data cleaning and imputation (e.g., using numpy and pandas libraries to improve quality of tracker datasets).

• Implement automated data management processes using Python and SQL to develop datasets for reporting and mining.

• Support ad hoc data reporting needs of all groups and data query components.