The analyst will be responsible for engaging with stakeholders and customers to gather requirements for the design and development of data models and design specifications using star schema techniques; analyze and create Extract-Transform-Load (ETL) specifications. Day to day responsibilities includes:
- Responsible for data warehouse design and development including conceptual, logical and physical data models, data analysis, data profiling, and ETL design.
- Working closely with client to assist in managing data needs, and supporting collection of data needed for various operational needs.
- Data analysis, problem solving, investigation and creative thinking with massive amount of data supporting variety of operational scenarios
- Respond to data queries/analysis requests from various groups within an organization. Create and publish regularly scheduled and/or ad hoc reports as needed.
- Responsible for the analysis and design of data marts for the Enterprise Data Warehouse.
- Analyzing source system data to understand the data structures, definitions and anomalies.
- Researching and documenting data definitions for all subject areas and primary data sets supporting the core business applications.
- Support development staff in their implementation of the reports and universes
- Provide data analysis for understanding and interpreting various operational data for the organization.
- Analyze and capture meaningful and operationally actionable information from very large scale relational database.
- Experience programming in Java.
- Open source contributions to data oriented and visual framework projects.
- Experience with Solr.
- Experience with Agile/Scrum.
MUST BE A US CITIZEN AND ABLE TO OBTAIN A CBP BACKGROUND INVESTIGATION
- Ability to work in high-pressured, tight-deadline environment.
- Excellent communication; good listener and able to clearly communicate ideas
- Strong initiative: must be able to take high-level requirement, ask questions/get clarifications, and get the job done. No handholding.
- Must be able to multitask efficiently and progressively and work comfortably in an ever-changing data environment.
- Must work well in a team environment as well as independently.
- Must be able to work flexible hours as dictated by work streams; night and weekend hours, overtime as needed by project