Design, build, and maintain automated data quality and validation frameworks. Collaborate with data engineering to profile, cleanse, and validate ETL pipelines using Alteryx, Python, and SQL in Snowflake. Monitor metrics, report issues, define data quality rules, troubleshoot problems, document processes, and mentor junior staff.
Position Overview We are seeking an experienced Senior Data Quality Engineer with strong expertise in ETL processes, Snowflake data warehousing, Alteryx workflows, and Python scripting. The ideal candidate will be responsible for ensuring the accuracy, reliability, and consistency of data across various platforms and will work closely with data engineering and analytics teams to develop and maintain automated data quality frameworks. Key Responsibilities • Design, develop, and maintain automated data quality and validation frameworks to ensure the integrity of data pipelines. • Collaborate with data engineering teams to understand ETL processes and identify potential data quality issues. • Perform data profiling, cleansing, and validation using tools such as Alteryx and custom Python scripts. • Build and optimize data quality checks and tests in Snowflake environments. • Monitor data quality metrics and generate reports to highlight data issues and trends. • Work with stakeholders to define data quality rules and standards. • Troubleshoot and resolve data quality issues in a timely manner. • Document data quality processes, standards, and best practices. • Mentor junior team members and contribute to process improvements. Required Skills and Qualifications • Bachelor's or master's degree in computer science, Information Technology, or a related field. • Proven experience as a Data Quality Engineer, Data Analyst, or similar role. • Strong experience with ETL processes and tools. • Expertise in Snowflake data warehousing platform. • Hands-on experience with Alteryx for data preparation and automation. • Proficient in Python scripting for data validation, automation, and testing. • Strong SQL skills for querying and data manipulation. • Knowledge of data governance and data quality frameworks. • Excellent analytical, problem-solving, and communication skills. • Ability to work independently and collaboratively in a fast-paced environment.
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