Senior Data Analyst

Job Title : Senior Data Analyst Location : Tempe, Arizona | Indianapolis, Indiana | Hartford, Connecticut | Raleigh, North Carolina | Richardson, Texas Job Type : Permanent Job Description Required Qualifications : Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education. At least 4 years of Information Technology experience Experience as a Data Analyst with a strong SQL background. Develop, optimize, and execute complex SQL queries for data extraction, analysis, and reporting. Proficiency in SQL Server, Snowflake, Netezza, or similar database platforms. Expertise in data modeling, normalization, and de-normalization techniques. Knowledge on ETL processes, data warehousing, and reporting tools. Strong analytical and problem-solving skills to assess complex data structures. Ability to work with Agile methodologies and collaborate in cross-functional teams. Experience working with US Healthcare Data. Hands-on experience with data governance, compliance, security protocols, Data Analysis and Data Visualization Tools. Perform requirement gathering and business analysis, working closely with stakeholders to define technical specifications. Preferred Qualifications : Understand and interpret data models, supporting data structuring and optimization initiatives. Collaborate with business and IT teams to translate business requirements into technical specifications. Good to have proficiency in Python or other scripting languages for additional data analysis capabilities. Perform database normalization and de-normalization to support efficient data storage and retrieval. Conduct complex database joins, including Common Table Expressions (CTEs), row qualification, and de-duplication techniques. Analyze large-scale SQL queries (1000+ lines) to ensure efficiency, accuracy, and optimization. Evaluate Tableau and Power BI reports, analyzing underlying queries to identify and refine reporting requirements. Develop source-to-target mapping based on established data models. Conduct gap analysis to identify inconsistencies and opportunities for data improvement. Perform data profiling to detect anomalies, assess data behavior, and highlight data discrepancies. Ensure effective communication across business and technical teams. Work in an Agile environment, adapting to dynamic project needs and timelines. Demonstrate quick learning ability to adopt new technologies and methodologies efficiently.