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