

Tential Solutions
Data Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Data Analyst position for a contract length of "unknown," with a pay rate of "unknown," located in "unknown." Key skills include SQL, R, Python, Tableau, and experience with data analytics tools. Strong problem-solving and documentation skills are required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 5, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Tysons Corner, VA
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🧠 - Skills detailed
#Data Quality #Tableau #Dataiku #Databricks #SPSS (Statistical Package for the Social Sciences) #Data Integrity #SQL (Structured Query Language) #Python #R #Data Manipulation #VBA (Visual Basic for Applications) #Data Analysis #SAS #Documentation
Role description
Job Summary
We are looking for a professional with strong problem solving and data analytics talent and experience to join our Reporting team. As a Data Analyst, you will leverage analytic and technical skills to design, build, and maintain well-managed data solutions and capabilities which address business problems and help regulatory staff make better informed decisions.
• Executing analytics projects including non-analytical tasks, such as data sourcing, documentation etc.
• Translating complex business sets and membership data into meaningful dashboards and insights, leveraging tools such as Microsoft PowerBI, Tableau, Cognos Analytics, Visual Basic for Applications (VBA),etc.
• Use of data analytics processing tools such as Dataiku, Domino, and Databricks
• Accessing and compiling large volumes of custom and syndicated data from disparate sources into concise and precise information
• Developing process maps for complex business functions and documenting business requirements to support project needs
• Leveraging existing data using analytical tools and languages (SQL, R, Python, SAS, or SPSS) to perform data manipulation and analysis
• Designing and developing data-driven analysis using statistical & advanced analytics methodologies to solve business problems
• Collaborating closely with developers to provide proofs of concept that can be converted into production-level applications
• Presenting prototypes and learnings to stakeholders at all levels across the organization
• Leveraging experience to ensure consistent data quality
• Performing research to gain context and meaning of uncultivated data sets
• Supporting the importance of data processes, data integrity and cleanliness, and the strategic use of data
#DICE
Job Summary
We are looking for a professional with strong problem solving and data analytics talent and experience to join our Reporting team. As a Data Analyst, you will leverage analytic and technical skills to design, build, and maintain well-managed data solutions and capabilities which address business problems and help regulatory staff make better informed decisions.
• Executing analytics projects including non-analytical tasks, such as data sourcing, documentation etc.
• Translating complex business sets and membership data into meaningful dashboards and insights, leveraging tools such as Microsoft PowerBI, Tableau, Cognos Analytics, Visual Basic for Applications (VBA),etc.
• Use of data analytics processing tools such as Dataiku, Domino, and Databricks
• Accessing and compiling large volumes of custom and syndicated data from disparate sources into concise and precise information
• Developing process maps for complex business functions and documenting business requirements to support project needs
• Leveraging existing data using analytical tools and languages (SQL, R, Python, SAS, or SPSS) to perform data manipulation and analysis
• Designing and developing data-driven analysis using statistical & advanced analytics methodologies to solve business problems
• Collaborating closely with developers to provide proofs of concept that can be converted into production-level applications
• Presenting prototypes and learnings to stakeholders at all levels across the organization
• Leveraging experience to ensure consistent data quality
• Performing research to gain context and meaning of uncultivated data sets
• Supporting the importance of data processes, data integrity and cleanliness, and the strategic use of data
#DICE






