As a Senior Data Quality, you will be responsible for ensuring the accuracy, reliability, and consistency of data across the organization. You will lead efforts to develop, implement, and enforce data quality standards and processes. This role involves working closely with data analysts, data engineers, business intelligence teams, and stakeholders to improve data quality and provide insights for effective decision-making. Key Responsibilities:Develop and implement data quality frameworks, guidelines, and best practices to ensure accurate and consistent data across multiple systems and data sources. Conduct regular data validation, cleansing, and deduplication efforts to ensure data integrity and quality. Design, implement, and execute data quality tests and audits to identify issues and areas for improvement. Monitor key data quality metrics and ensure compliance with data quality standards. Investigate data quality issues, identify root causes, and implement corrective actions in collaboration with engineering, analytics, and business teams. Collaborate with stakeholders to improve data collection processes, define data quality KPIs, and recommend enhancements in data workflows. Maintain thorough documentation of data quality processes, rules, and guidelines. Create data dictionaries, data flow diagrams, and process maps. Work closely with data engineers, data architects, and business intelligence teams to improve data pipelines, ETL processes, and data governance efforts. Develop and implement automated solutions for data profiling, validation, and monitoring to enhance data quality operations. Communicate data quality status, issues, and improvement plans with stakeholders, ensuring alignment on data governance goals. Key Qualifications:Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, or related fields. Experience:3+ years of experience in a data quality, data engineering, or similar role. Proven track record of managing and improving data quality in large-scale data environments. Technical Skills:Proficiency in SQL and experience with relational databases. Experience with data quality tools and frameworks (e.g., Informatica Data Quality, Talend, Collibra, etc.). Strong knowledge of ETL processes, data warehousing, and data governance principles. Knowledge of scripting languages such as Python, R, or similar. Soft Skills:Strong analytical and problem-solving abilities. Excellent communication and collaboration skills, with the ability to interact with technical and non-technical stakeholders. Attention to detail and a commitment to data accuracy. Preferred Qualifications:Certifications in data management or quality tools (e.g., CDMP).