Job Description

Insight Global is looking for a Data Sampling Analyst to join a large financial client in the Uptown area. On a typical day, you will collaborate with business stakeholders to understand data requirements for testing, and then write and execute SQL queries to extract and prepare the necessary data samples. A significant part of your time will be spent validating the accuracy and completeness of the sourced data and building and refining data populations based on defined criteria and sampling governance requirements. You will also partner with test execution teams to understand their needs and assist in writing any extra procedures related to data sampling, attend meetings with stakeholders to discuss data requirements, testing strategies, and results, and document data sourcing procedures, sampling methodologies, and data validation steps. Additionally, you will troubleshoot data-related issues and work to resolve discrepancies, contribute to the design and assessment of the quality of both manual and automated tests from a data perspective, and continuously learn and adapt to new data sources and technologies.

Must Haves:

• Strong SQL Proficiency: Demonstrated experience writing complex SQL queries to extract, manipulate, and analyze large datasets from various sources.
• Experience with Large Datasets: Ability to work effectively with large volumes of data from different data sources.
• Data Validation Skills: Proven ability to validate data sourcing and ensure data accuracy and integrity.
• Analytical and Problem-Solving Skills: Strong ability to research, analyze, and solve complex data-related problems.
• Communication Skills: Excellent written and verbal communication skills to effectively interact with technical and non-technical stakeholders.
• Ability to Work Independently: Proven ability to think and work independently, translating business objectives into comprehensive test requirements.
• Partnership and Collaboration: Ability to partner effectively with Test Developers and other stakeholders.

Plusses:

• Python Experience: Familiarity with Python for data manipulation and analysis.
• Knowledge of Data Warehouse and Mining Concepts: Understanding of data warehousing principles and data mining techniques.
• Experience with Third-Party Data Sources: Familiarity with accessing and acquiring data from external sources.

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