• Analyze large data sets to gain an understanding of the data, discover data anomalies, and look for ways to leverage data in support of company mission.
• Integrate data from disparate sources to help define an enterprise data dictionary.
• Define and populate conceptual and logical data models, data dictionaries and metadata repositories.
• Document key business processes, technical requirements and data transformations.
• Maintain relationships with business and technical staff across the enterprise to understand data requirements and usage patterns.
• Become the Subject Matter Expert in the Domain
•Required Skills and Qualifications:
• Understand logical, physical and conceptual data models.
• Able to design both OLTP and dimensional data models well
• Strong SQL, including analytic functions.
• Strong verbal and written communication skills – must be able to stand up and defend model and data analysis to team members
• Able to elicit requirements from business users and convey them clearly to technology teams.
• Able to explain data models, requirements and quality issues to non-data savvy users.
• Solid foundational knowledge of data warehousing, metadata management, and master data management (MDM).
• Experience with data profiling, cleansing and transformation.
• Ability to create data scenarios and explain data transformations
Preferred Skills and Qualifications
• Define data specifications or data models for a large department or enterprise.
• Business analysis work using process modeling and conceptual data modeling.
• Experience with process modeling methodologies (e.g., RUP, CMMI, BPM, User Stories).
• Experience in an Agile/SCRUM environment.
• Experience with master data management (MDM), data governance and data quality management.
Plus Skills and Qualifications:
• Industry knowledge – prior experience at a broker-dealer firm, SEC or other financial agency.
• Experience with big data, Hadoop, NoSQL databases
• Experience with document management metadata
• Basic understanding of Statistics and its usage in data analysis
• Exposure to statistical languages like R