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Tier-1 brand plus metro context increases applicants but senior niche reduces overall density.
Core data quality skills transfer across industries, though BFSI domain knowledge is only preferred.
Explicit 8+ years requirement plus specific Azure, DQ tools, and mentorship needs make filters strict.
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Ensure data quality of production grade data and analytics solutions by building and maintaining validation rules and test cases across accuracy, completeness, consistency, and timeliness.
Perform data quality checks at various lifecycle stages (unit testing, integration testing, user acceptance testing), conduct data profiling to detect anomalies, and create/maintain data quality artifacts.
Independently lead design, solutioning, and estimations for data quality initiatives and mentor Data Quality Analysts.
8-10+ years of relevant experience in data quality or data analytics roles.
Bachelor’s degree in computer science, information technology or equivalent.
Proficiency in SQL, Azure Data Services (Data Factory, Synapse), data quality testing tools (Atacama, IDQ), and ETL tools like Tosca.
Experience with data profiling, cleansing, working with large data sets in On-Prem and Cloud environments, and mentoring experience.
Experienced individual contributor comfortable independently leading design and solutioning for wide ranging business problems related to data quality.
Skilled in collaborating with cross-functional teams across Business, Technology, Operations, and Data & Analytics capabilities.
Domain exposure to Banking/Financial Services/Insurance is a plus along with familiarity with Gen AI technologies and NoSQL/HIVE databases.