Data Quality Engineer II

Job Description

Responsibilities Conduct thorough data profiling and analysis to identify anomalies, inconsistencies, and inaccuracies in datasets Automate processes, data quality checks, and workflows to ease data validation processes across complex, interdependent data systems Develop generic quality check frameworks that can be utilized across multiple products Develop and execute comprehensive data quality testing strategies and plans to verify the implementation of data pipelines and data validations. Design and implement intuitive metrics that show stake holders the health of their data in an actionable format Conduct initial root cause analysis for data issues, collaborate with partners to clearly identify the issue, scope and impact, and path for research/solutioning Create and maintain documentation related to data quality processes and standards Reporting Establish monitoring mechanisms to proactively identify data quality issues, and generate regular reports on data quality metrics for review Collect data quality requirements from key partners, seeking to understand the subjective quality measures that are important to data consumers to build and maintain trust in our data products Ideal Candidate Qualifications: 3+ years of experience in the DataQuality / DataModeling / DataEngineering fields Extensive Python or R experience to develop and maintain data quality scripts, tools, and frameworks. Expert-level knowledge of SQL for complex data querying and manipulation Experience with analytical and predictive models Experience with various ETL transformations and workflows Experience working in Hadoop big data environments Strong understanding of data quality concepts, methodologies, and best practices. Strong collaboration skills and ability to work effectively in a cross-functional, interdependent team environment Keen sense of prioritization and ability to time Superior academic record with a degree in a technical field Strong written and verbal English communication skills