Data Quality Engineer

delartech; Menlo Park (CA); On-site; USD 125,000 - 170,000; Full time

Job summary

Delart is seeking a Data Quality Engineer to safeguard benchmark data integrity across large-scale device testing. You will implement validation plans, automate checks in Python, and own analytics reporting for product engineering teams.

You’ll run daily reviews of 50+ devices, troubleshoot automation issues, and help scale data-quality standards across lab operations and testbeds. A strong background in data analysis and CI/CD is essential.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related technical discipline.
• 5+ years of hands-on experience in data quality engineering, QA automation, test engineering, data analysis, or similar roles.
• Proficiency with Python for automation, test scripting, and advanced data analysis (including debugging and maintaining codebases).
• Solid knowledge of SQL for querying, inspecting, and validating measurement and test-run data.
• Experience building and operating automated data-quality checks, dashboards, alerting, or reporting.
• Experience with CI/CD-driven test infrastructures or modern data pipelines.
• Strong troubleshooting ability across software, configuration, environment, and hardware domains.
• Excellent written and verbal communication for technical reporting.

Responsibilities

• Define and implement data-quality checks, acceptance criteria, and validation plans grounded in benchmarking requirements and product-team expectations.
• Run daily operational reviews of 50+ devices under continuous test automation, investigating anomalies and lab variances.
• Systematically validate large-scale benchmark datasets, using statistical analyses to identify regressions and misaligned results.
• Develop, deploy, and maintain automated data-quality checks, alerting systems, and dashboards to track data integrity and trends.
• Generate and communicate analytical reports on benchmarking outputs, highlighting quality risks and actionable findings.
• Build Python-based automation and tooling for continuous benchmarking across multiple device form factors.
• Investigate root causes of anomalous data and distinguish genuine performance from artifacts.
• Review video capture logs to validate outcomes and troubleshoot scenario failures.
• Operate and monitor CI/CD-driven test environments, ensuring stability and rapid issue resolution.
• Document validation protocols, triage guides, and reporting workflows for scalable operation.
• Collaborate with lab ops, networking, and product teams to establish data-quality standards.

Skills

Data quality experience

Data validation

Troubleshooting

Communication

Mentoring

Device benchmarking

CI/CD pipelines

Automation

Test scripting

Education

Bachelor's degree in Computer Science or related field

Master's degree in Data Science/CS/EE

Tools

Python

SQL

Appium

Job description

About the job

Delart is home to a team of world-class engineers and project leaders dedicated to developing the next generation of advanced networking technologies, consumer devices, and innovative technology solutions. Trusted by some of the world's leading technology companies, we deliver highly scalable, mission-critical solutions that power both consumer and business applications globally. Since our founding in 2017, we have been at the forefront of designing cutting-edge networking, telecommunications, and consumer products, while driving end-to-end project execution and creating transformative technology applications.

Overview

Join our team as a Data Quality Engineer, where you'll be the guardian of benchmark data integrity supporting continuous large-scale device testing operations. This hands-on role combines advanced data analysis, Python-based test automation, and operational ownership, ensuring the health, reliability, and actionable insights of benchmark datasets used by product engineering teams.

Responsibilities

• Define and implement data-quality checks, acceptance criteria, and validation plans grounded in benchmarking requirements and product-team expectations.
• Run daily operational reviews of 50+ devices under continuous test automation-investigating anomalies, debugging automation issues, and addressing lab-environment variances.
• Systematically validate large-scale benchmark datasets, leveraging statistical analysis to identify regressions, anomalies, and misaligned results.
• Develop, deploy, and maintain automated data-quality checks, alerting systems, and interactive dashboards to track data integrity, device health, and operational trends.
• Generate, review, and communicate clear analytical reports on benchmarking outputs, highlighting quality risks and actionable findings for stakeholders.
• Build and support Python-based automation and operational tooling for continuous benchmarking and data validation across multiple device form factors, collaborating directly with scenario and platform developers.
• Conduct in-depth investigations and monthly analytics to diagnose the root cause of anomalous data, distinguishing genuine device performance from automation artifacts.
• Review video capture logs from test runs to validate outcomes and troubleshoot scenario failures.
• Methodically debug data discrepancies, triaging systematically across lab configuration, application settings, wireless conditions, and device defects, and escalating issues to the proper owners.
• Operate and monitor CI/CD-driven test environments, ensuring stability and rapidly resolving operational failures.
• Document validation protocols, triage guides, and reporting workflows to facilitate operation at scale.
• Collaborate closely with lab operations, networking, and product teams to address environment and device issues, and help establish robust data-quality standards and practices.

Minimum Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related technical discipline.
• 5+ years of hands-on experience in data quality engineering, QA automation, test engineering, data analysis, or similar roles.
• Demonstrated expertise in validating large datasets, identifying anomalies and regressions with statistical techniques, and clearly communicating findings to stakeholders.
• Proficiency with Python for automation, test scripting, and advanced data analysis (including debugging and maintaining codebases).
• Solid knowledge of SQL for querying, inspecting, and validating measurement and test-run data.
• Prior experience developing and operating automated data-quality checks, dashboards, alerting, or analytical reporting.
• Experience working with CI/CD-driven test infrastructures or modern data pipeline environments, monitoring system stability and resolving failures.
• Strong troubleshooting ability, with a record of isolating root causes across software, configuration, environment, and hardware domains.
• Excellent written and verbal communication, particularly for technical reporting and conveying quality risks to engineering and product stakeholders.

Preferred Qualifications

• Master's degree in Data Science, Statistics, Computer Science, Electrical Engineering, or closely related field.
• Hands-on experience with device benchmarking or quality-of-experience measurement platforms, including workflows involving video result validation.
• Familiarity with mobile test automation frameworks (e.g., Appium) and deep understanding of mobile application behavior.
• Experience diagnosing environmental, RF, or hardware-related variables in device testing labs.
• Operational experience managing device fleets, provisioning, and supporting large-scale testbeds.
• Demonstrated history of mentoring junior engineers and championing best practices for data quality.

CA Base Pay $125,000 - $170,000 USD

Benefits

Delart provides competitive benefits and compensation across all regions where we operate.