Data Quality Engineer

Description

The company designs networking, telecommunications, and consumer products, and builds scalable, mission-critical solutions for leading technology firms. Founded in 2017, it manages projects from start to finish.

This hands-on role protects the quality of benchmark data from continuous large-scale device testing. You will combine data analysis, Python test automation, and day-to-day operations to keep benchmark datasets reliable and useful for product engineering teams.

Responsibilities

• Set up data-quality checks, acceptance criteria, and validation plans based on benchmarking requirements and product team expectations.
• Review daily the status of more than 50 devices running continuous test automation, investigating anomalies, fixing automation bugs, and handling lab environment differences.
• Check large benchmark datasets with statistical methods to find regressions, anomalies, and results that do not line up.
• Build, release, and maintain automated data-quality checks, alerts, and interactive dashboards that track data integrity, device health, and operational trends.
• Run in-depth investigations and monthly analytics to find the root cause of anomalous data and separate real device performance from automation artifacts.
• Write, check, and share clear analytical reports on benchmark results that flag quality risks and actionable findings for stakeholders.
• Build and support Python automation and operational tools for continuous benchmarking and data validation across several device form factors, working directly with scenario and platform developers.
• Review video capture logs from test runs to confirm outcomes and troubleshoot scenario failures.
• Work through data discrepancies systematically, checking lab configuration, application settings, wireless conditions, and device defects, then pass issues to the right owners.
• Run and monitor CI/CD-driven test environments, keeping them stable and fixing operational failures quickly.
• Document validation protocols, triage guides, and reporting workflows so operations can scale.
• Work closely with lab operations, networking, and product teams on environment and device issues, and help set robust data-quality standards and practices.

Requirements

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field.
• 5+ years of hands-on experience in data quality engineering, QA automation, test engineering, data analysis, or similar work.
• Proven ability to validate large datasets, find anomalies and regressions using statistical techniques, and explain findings clearly to stakeholders.
• Proficiency in Python for automation, test scripting, and advanced data analysis, including debugging and maintaining codebases.
• Solid SQL skills for querying, inspecting, and validating measurement and test-run data.
• Past experience building and running automated data-quality checks, dashboards, alerts, or analytical reports.
• Experience with CI/CD-driven test infrastructure or modern data pipelines, monitoring stability and fixing failures.
• Strong troubleshooting skills, with a track record of isolating root causes across software, configuration, environment, and hardware.
• Excellent written and verbal communication, especially for technical reports and explaining quality risks to engineering and product stakeholders.
• Preferred: Master's degree in Data Science, Statistics, Computer Science, Electrical Engineering, or a closely related field.
• Preferred: Hands-on experience with device benchmarking or quality-of-experience measurement platforms, including validating video results.
• Preferred: Familiarity with mobile test automation frameworks such as Appium and a deep understanding of mobile app behavior.
• Preferred: Experience diagnosing environmental, RF, or hardware variables in device testing labs.
• Preferred: Operational experience managing device fleets, provisioning, and supporting large-scale testbeds.
• Preferred: A history of mentoring junior engineers and promoting best practices in data quality.

Conditions

CA base pay is $125,000 to $170,000 USD.

The company is an equal opportunity employer and does not tolerate discrimination or harassment based on any legally protected characteristic.

Benefits

• In the United States, benefits include premium PPO and HMO medical insurance, dental and vision coverage, a flexible spending account (FSA), life insurance, short- and long-term disability insurance, a company-matched 401(k) plan, and generous paid time off.
• Compensation and benefits are competitive across all regions where the company operates.