Data Engineer at SIGMA SOFTWARE INC

Foster City, California, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Jan, 26

Salary

0.0

Posted On

07 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Python, SQL, Statistical Techniques, Machine Learning, Data Pipelines, Data Analysis, Safety Metrics, Event Triage, Cross-Functional Collaboration, Organizational Skills, Documentation, Geospatial Data Analysis, Business Intelligence Tools, Functional Safety Standards

Industry

IT System Custom Software Development

Description

As an AV Safety Data Engineer, you will play a critical role in developing and maintaining robust data infrastructure to surface safety-relevant interactions, assess AV events, and inform autonomy development through data-driven insights. You will build scalable pipelines and metrics that ensure we receive strong, reliable signals from data, directly influencing how we assess system readiness and accelerate safe deployment, while also supporting the crucial task of event triage and analysis. In this role you will: Develop and maintain miners that identify events of interest from fleet and simulation data. Improve the accuracy and efficiency of existing miners through advanced statistical and ML techniques, ensuring high signal quality. Build scalable data pipelines and dashboards to monitor miner performance, signal quality, and key safety metrics. Conduct exploratory data analyses to uncover trends, failure modes, and opportunities to improve vehicle behavior, specifically focusing on critical safety events and system anomalies. Triage and assess AV events including both system behavior and hardware related anomalies, for potential safety/legal/regulatory concerns or system gaps, using contextual judgment grounded in safety, legal, and engineering principles. Develop and maintain clear triage guidelines and criteria for both onshore and offshore triage teams. Support regulatory reporting processes by providing data and analysis as needed. Master’s Degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative or Engineering field such as Transportation Engineering, Systems Engineering, Civil Engineering, Mechanical Engineering, or Electrical Engineering. 6-8 years of experience working with safety-critical systems in AV, Automotive, Transportation Engineering, or a closely related industry. Strong programming skills in Python and SQL. Experience with large datasets and distributed data processing frameworks (e.g., Spark, Databricks). Strong data engineering skills, including data wrangling and expertise in building maintainable, scalable, and efficient data pipelines. Familiarity with statistics and probability, and experience with sampling and estimation methodologies. Proven ability to design metrics, run analyses, and translate findings into actionable recommendations. Strong understanding of behavioral safety concepts and the ability to interpret vehicle behavior in real-world contexts, along with knowledge of AV requirements, road user behavior, and traffic regulations. Experience working with cross-functional teams and clearly communicating technical content to both engineering and non-technical audiences. Strong organizational skills with attention to detail, especially in process development and documentation related to data pipelines and safety analysis. Bonus Qualifications PhD in Engineering or a related technical field. Prior experience with AV safety or system behavior triage. Experience with geospatial data analysis. Experience with business intelligence tools (e.g., Looker) to support analysis. Familiarity with ISO 26262 or other functional safety standards Health Care Plan (Medical, Dental & Vision) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Training & Development Retirement Plan (401k, IRA) Free breakfast and lunch

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Responsibilities

The Data Engineer will develop and maintain data infrastructure to assess AV events and inform autonomy development. This includes building scalable pipelines and conducting exploratory data analyses to improve vehicle behavior and safety metrics.