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Analyze, clean, validate, and transform client-provided data from diverse sources and formats before system upload Execute SQL queries and Python scripts to process, reconcile, and validate large transactional datasets Investigate data quality issues, exceptions, and inconsistencies to present findings to project managers for client resolution Collaborate with internal teams and external stakeholders to resolve data-related issues and ensure accuracy Review project manager requests to determine data processing requirements and deliver processed datasets Recommend and implement process improvements that increase accuracy, consistency, and operational efficiency Requirements:
Bachelor's degree in Computer Science, Statistics, Data Analytics, Mathematics, Business, or related field Proven experience as a data analyst working with structured datasets, particularly large record-based or transactional data Proficiency in Python (preferably pandas) for data cleaning, transformation, validation, and reconciliation Strong SQL skills for data extraction, joining, filtering, aggregation, and validation Demonstrated ability to identify and resolve data quality issues including duplicates, missing values, and record inconsistencies Benefits:
Competitive pay Generous health and wellness benefits Retirement savings plans Parental leave
Languages
- English
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