Senior Data Analytics Engineer, Hardware Quality

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 173,000 - 203,000; Full time

Benefits offered by this job

Competitive salary

Equity

Health, dental, vision

Mental health resources

Paid time off

Sick and parental leave

Employee discounts

Job summary

United States Digital Space LLC is seeking a Senior Quality Data Engineer – Hardware to join our Hardware Quality Engineering team in San Francisco. You will analyze manufacturing, test, telemetry, warranty, and field data to uncover quality trends and drive improvements across engineering and manufacturing.

The role requires strong SQL and Python, with experience turning large datasets into actionable insights, and collaboration across Hardware, Quality, Reliability, Firmware, Operations, and

Qualifications

• 5+ years of experience working with data in engineering, manufacturing, quality, reliability, or related technical environment.
• Strong SQL skills and Python for data analysis and automation.
• Experience with large datasets and turning ambiguous engineering or product questions into structured analysis.
• Experience with manufacturing, hardware test, reliability, warranty, field, or product data.
• Working knowledge of statistics and evaluating trends and correlations.

Responsibilities

• Analyze manufacturing, factory test, device telemetry, field, warranty, and failure analysis data to identify quality trends and emerging issues.
• Connect data across manufacturing systems, test logs, device telemetry, and field returns to understand relationships between build, test, and field performance.
• Support failure investigations by identifying patterns and correlations linking field failures to manufacturing processes or product behavior.
• Compare failed vs. known-good populations to spot signals associated with downstream failures.
• Analyze testing parameters to identify marginal passes and opportunities to improve screening/detection.
• Build cohort-based warranty and field-quality analyses across product, build, factory, and time in field.
• Apply statistics to separate meaningful signals from normal variation for data-driven decisions.
• Develop monitoring and early-warning indicators to catch issues before large problems arise.
• Collaborate with Quality and Engineering to validate findings through experiments and measure corrective actions.
• Identify gaps in data quality and work with teams to resolve them.
• Create scalable analytics, dashboards, and automated reports for visibility.

Skills

SQL

Python

Data analysis

Statistics

Manufacturing data

Cross-functional collaboration

Communicate findings

AI/ML data validation

Tools

Tableau

Databricks

AWS

dbt

Athena

Job description

Our mission at the company is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their the company Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are looking for a Senior Quality Data Engineer – Hardware to join our Hardware Quality Engineering team.

In this role, you will bring together manufacturing, test, device telemetry, field, warranty, and failure analysis data to understand how our products are performing and where we can improve. You will work closely with engineering and manufacturing teams to identify quality trends, investigate failures, improve detection, and help prevent known issues from reaching customers.

This is a hands-on role for someone who enjoys working at the intersection of hardware and data. You will work closely with Hardware Engineering, Quality, Manufacturing, Reliability, Firmware, Operations, and Data teams.

What you will do

• Analyze manufacturing, factory test, device telemetry, field, warranty, and failure analysis data to identify quality trends and emerging issues.

• Connect data across manufacturing systems, test logs, device telemetry, and field returns to understand relationships between how a product was built, how it performed during test, and how it performs in the field.

• Support failure investigations by identifying patterns and correlations that help connect field failures back to manufacturing processes, components, test results, or product behavior.

• Compare failed and known-good populations to identify manufacturing, test, telemetry, or component signals associated with downstream failures.

• Analyze manufacturing and final test parameters to identify marginal passes, abnormal trends, and opportunities to improve screening and escape detection.

• Build cohort-based warranty and field-quality analysis across product, build, factory, component, configuration, and time in field.

• Apply statistical methods to separate meaningful product and process signals from normal variation and help teams make data-driven quality decisions.

• Develop monitoring and early-warning indicators that help identify emerging quality issues before they become larger field or warranty problems.

• Partner with Quality and Engineering teams to validate findings through failure analysis, controlled builds, additional inspection, or process experiments, and measure whether corrective actions are working.

• Identify gaps in manufacturing and quality data, including missing data, inconsistent definitions, traceability gaps, or conflicting metrics, and work with the appropriate teams to resolve them.

• Build scalable analytics, dashboards, and automated reporting that give engineering teams clear visibility into product and manufacturing quality.

• Partner with Data Engineering and Data Science teams when new data pipelines or infrastructure are needed while owning the Hardware Quality use cases and analysis.

• Communicate findings clearly and turn complex datasets into conclusions and recommendations that engineering teams and leadership can act on.

We would love to have you on our team if you have

• 5+ years of experience working with data in engineering, manufacturing, quality, reliability, operations, or a related technical environment.

• Strong SQL skills and hands‑on experience with Python for data analysis and automation.

• Experience working with large datasets and turning ambiguous engineering or product questions into structured analysis.

• Experience with manufacturing, hardware test, reliability, warranty, field, or product data.

• Working knowledge of statistics and experience comparing populations, identifying correlations, and evaluating trends.

• Experience building analytics and visualizations using Tableau, Databricks, or similar tools.

• Strong problem‑solving skills and curiosity to understand why a product or process is behaving the way it is.

• Ability to work effectively across Hardware, Manufacturing, Firmware, Quality, Reliability, and Data teams.

• Ability to communicate technical findings clearly to both engineering teams and leadership.

• Experience validating data outputs from AI/ML models to manufacturing data sets via python, athena data analysis

What makes you stand out

• Experience with consumer electronics, wearables, IoT, medical devices, or other high-volume hardware products.

• Experience working with manufacturing test data, MES, serialized device traceability, factory process data, or device telemetry.

• Experience analyzing warranty, RMA, reliability, or field-return data.

• Experience correlating manufacturing or test parameters with downstream product failures.

• Understanding of hardware test, manufacturing processes, failure mechanisms, battery behavior, or electrical systems.

• Experience with statistical process control, anomaly detection, predictive analytics, or similar techniques applied to hardware or manufacturing problems.

• Familiarity with Databricks, Tableau, AWS, dbt, or similar data and analytics platforms.

Benefits

At the company, we care about you and your well‑being. Everyone here at the company has a ring of their own and we are continually looking to improve employee health.

What we offer:

• Competitive salary and equity packages

• Health, dental, vision insurance, and mental health resources

• An the company Ring of your own plus employee discounts for friends & family

• 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off

• Paid sick leave and parental leave

the company takes a market‑based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job‑related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

• Region : $172,550- $203,000