Senior Data Analyst/Data Warehouse Consultant

Required Skills & Abilities:

• 3­ + years' experience relational Database Modeling (conceptual, logical, and physical)

• Tools:

Microsoft Visual Studio,

Microsoft SQL Server,

Azure SQL Server,

SSIS, SSRS,

Power BI Report Server, Power BI Service,

SSMS: 6-7 years' experience;

• Tools: Quest Erwin or similar data modeling tool – 1 year experience

Responsibilities

• • Creation of IT data models (e.g., conceptual, logical, physical, canonical);

• • Implementation of data design and transformation procedures;

• • Creation of frameworks for representing data elements;

• • Resolution of conflicts between data models;

• • Design, creation, and maintenance of relational and dimensional databases and data systems;

• • Recommendation and implementation of data reliability, efficiency, and quality improvements.

• • Enhancements to existing database systems to increase operating efficiency or adapt newer requirements;

• • Recommendation and implementation of data reliability, efficiency and quality improvements;

• • Adherence and contribution to work plan timelines, managing workflows to meet project timeframes;

• • Design and creation of data processing systems that combine core data sources into data repositories

• • Map documentation of data elements from UI screens to database, mapping between 2 databases.

• • Data conversions, imports, and exports of data within and between internal and external systems;

• • Develop data migration scripts for loading data from "old" system to "new" target system(s).

• • Develop data transformation and automation processes supporting business systems

• and data flows;

• • Maintain data repositories quality by adding, modifying, and deleting data as needed and as requested;

• • Troubleshoot data issues and data processing tools, systems, and software;

• • Identify and resolve problems related to database management systems;

• • Develop and maintain a query library to support recurring data requests;

• • Maintain data dictionaries and other related data processing metadata;

• • Implement statistical models to identify trends, correlations, and patterns in data sets;

• • Catalog data sources;

• • Perform data cleansing and filtering;

• • Design analytical dashboards and reports;

• • Mine and analyze multiple data sets (Dimensional) for trends, insights, problems, etc;

• • Document models, solutions, data mapping, technical specifications, data dictionaries,

• test cases, etc.;