The Data Reliability Engineer will use tools and processes, assess data accuracy for critical pipelines and data points, build dashboards to report on that accuracy including statistical analysis, assist engineering and analyst teams with data quality issue remediation, and track data quality issue remediation.

What You'll do:

• Data Accuracy Testing - Work with engineering teams to define data accuracy for different data points, create a plan to assess that accuracy, execute that plan, and monitor and present results.
• Data Quality Issue Tracking and Remediation - Work with engineering teams to diagnose data quality issues, develop remediation plans, build out new testing to detect issues like this in the future, and track issues at scale to get a better understanding of the overall data quality of our data products.
• Data Quality Rule Creation - Work with SMEs to determine quality policies to be applied to data assets. Work with Data Engineers as needed to create views or tables when more complex ETL is needed. Rules are generally written using SQL.
• Data Quality Tool Administration - The DRE will be the administrator for the data quality tools, including management of rules and policies being written in the data quality tool. The DRE will work with Data Engineers to build any integrations or processes necessary to make the data quality tools useful.

What you bring:

• Bachelor’s degree in a relevant field or equivalent work experience
• 5+ years of data experience
• 5+ years of SQL experience
• 1+ years of BI Tool experience
• 1+ years of data pipeline / orchestration experience (ex., Apache Airflow)
• 1+ years of distributed computing experience (ex., Apache Spark)
• 2+ years of Statistics experience/exposure (through college coursework or work experience)
• Some Python experience is preferred
• Some distributed query tool experience is preferred (i.e., Apache Trino)
• Data Research process experience is preferred

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