Aumovio Logo

Aumovio

Principal / Senior Engineer, Data Analytics & Management, Technical Operations Management

Posted One Month Ago
Be an Early Applicant
In-Office
Singapore, SGP
Senior level
In-Office
Singapore, SGP
Senior level
Lead semiconductor manufacturing analytics: own test analytics strategy, build analytics platforms, implement quality screening (PAT, SBL, outlier detection), integrate foundry/OSAT/MES systems, design data infrastructure and automation (ETL, dashboards), and drive operational excellence across wafer, assembly, test, and quality.
The summary above was generated by AI
Company Description

Since its spin-off in September 2025 AUMOVIO continues the business of the former Continental group sector Automotive as an independent company. The technology and electronics company offers a wide-ranging portfolio that makes mobility safe, exciting, connected, and autonomous. This includes sensor solutions, displays, braking and comfort systems as well as comprehensive expertise in software, architecture platforms, and assistance systems for software-defined vehicles. In the fiscal year 2024 the business areas, which now belong to AUMOVIO, generated sales of 19.6 billion Euro. The company is headquartered in Frankfurt, Germany and has about 87.000 employees in more than 100 locations worldwide.

Job Description

At AUMOVIO AESS, we are building the next generation of automotive semiconductor solutions that enable safer, smarter, and more connected mobility.

We are looking for a highly motivated Principal / Senior Engineer, Data Analytics & Management to join our growing Technical Operations Management (TOM) organization. The role will drive manufacturing intelligence, test analytics, quality screening, analytics platform development, digital transformation, and operational excellence across the semiconductor product lifecycle.

Candidates with strong knowledge in semiconductor data analytics and tools, outlier detection methodology (e.g.: PAT, SBL, cluster defect analysis) and data infrastructure setup is highly preferred.

Key Responsibilities

  • Test Analytics & Quality Screening
    • Own the test analytics strategy covering Wafer Sort (WS), Burn-In (BI) and Final Test (FT).
    • Develop advanced analytics solutions for yield learning, outlier detection, excursion monitoring, statistical screening, and quality monitoring.
    • Support implementation and optimization of quality screening methodologies including PAT, Statistical Bin Limits (SBL), dynamic guard-banding, clustering, and test escape prevention.
    • Collaborate with Product Engineering and Test Engineering teams to improve outgoing quality performance and reduce DPPM.
  • Analytics Platform Ownership
    • Own the manufacturing analytics platform ecosystem, e.g. JMP, Power BI, Databricks, and yield related tools.
    • Define platform roadmap, governance, deployment strategy, and user adoption plans.
    • Establish best practices for analytics development, data governance, reporting standards, and engineering productivity.
    • Provide technical leadership for tool evaluations, vendor engagement, implementation, and user training.
  • Fabless Operations Systems & Tool Setup
    • Define system requirements and integration strategies between Foundries, OSATs, MES, Quality Management Systems, and analytics platforms.
    • Drive standardization of manufacturing data flows, system interfaces, and engineering workflows.
    • Develop operational tools to support NPI, qualification, production ramp, and mass production activities, e.g. process release, deviation material management, change management.
  • Data Infrastructure & Automation
    • Own end-to-end semiconductor manufacturing data ecosystem across wafer, assembly, test and quality operations.
    • Design and manage manufacturing data solutions, including databases, ETL pipelines, dashboards, cloud architectures, and automated reporting systems.”
    • Develop automation solutions using Python, SQL, Power BI, VBA, and modern analytics technologies to improve engineering productivity.

 

    Qualifications

    Required:

    • Bachelor's, Master's, or PhD in Electrical Engineering, Electronics Engineering, Computer Science, Data Science, Statistics, or related fields.
    • Minimum 5+ years (Senior Engineer) or 8+ years (Principal Engineer) of semiconductor industry experience in data analytics, analytics platforms and data architecture.
    • Experience analyzing semiconductor manufacturing, yield, test, reliability, and quality datasets.
    • Hands-on experience with STDF, ATDF, MES, manufacturing databases, and semiconductor data ecosystems.
    • Self-motivated, hands-on team player with a strong ownership mindset, capable of delivering results in a dynamic and rapidly growing startup environment.
    • Strong collaboration, communication, and interpersonal skills, with the ability to work effectively across global and multicultural teams.
    • Excellent analytical and problem-solving skills, combining data-driven decision-making with sound engineering judgment.

    Technical Expertise:

    • Experience with Databricks, JMP, Yield tools or equivalent semiconductor analytics platforms.
    • Experience with Statistical Process Control (SPC), PAT, SBL, outlier detection, clustering analysis, and quality screening techniques.
    • Proficiency in SQL, Python, JMP, Power BI, Tableau, Excel/VBA, or equivalent analytics tools.
    • Experience leading digital manufacturing, analytics platform, AI-based analytics or data transformation initiatives.
    • Knowledge of ATE test operations and test methodologies.
    • Understanding of semiconductor manufacturing flows including Wafer Sort, Assembly, Final Test, Reliability, and Quality operations.

    Additional Information

    Ready to take your career to the next level? The future of mobility isn’t just anyone’s job. ​Make it yours! ​Join AUMOVIO. Own What’s Next.​

    Similar Jobs

    20 Minutes Ago
    In-Office
    Singapore, SGP
    Senior level
    Senior level
    Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
    Build and operate backend services for global liquidity, safeguarding, investment workflows and cash data. Design scalable systems for forecasting, cash positioning, fund movement and optimisation. Implement event-driven microservices (Kafka, gRPC/REST), persistence (Postgres/NoSQL), strong controls, testing, observability and on-call runbooks. Collaborate with Product, Treasury, Finance, Compliance and Data to deliver reliable, auditable, and highly available liquidity platform features.
    Top Skills: Ci/Cd PipelinesEvent-Driven WorkflowsGrpcJavaJvmKafkaKey-Value StoresKotlinLoggingMetricsMicroservicesNoSQLPostgresRest ApisSQLTracing
    30 Minutes Ago
    Hybrid
    Singapore, SGP
    Senior level
    Senior level
    Financial Services
    Owns regional and global payments and receivables initiatives from business requirements through execution. Leads market commercialization, client acquisition, and collaboration with Sales and functional partners. Defines end-to-end business architecture, service delivery models, systems flows, and detailed requirements for payment services. Partners with technology, operations, risk, compliance, legal, and service teams to deliver differentiated solutions and drive tactical execution.
    Top Skills: ExcelMicrosoft PowerpointMicrosoft VisioMicrosoft Word
    2 Hours Ago
    Hybrid
    Singapore, SGP
    Junior
    Junior
    Fintech • Mobile • Payments • Software • Financial Services
    Conduct due diligence and risk assessments for banks and online platform partners. Review KYC information, legal agreements, and compliance documentation; prepare compliance memos; manage partner onboarding; recommend risk-based monitoring controls; track regulatory developments; and collaborate with Legal, Risk Management, Business Development, and senior stakeholders on enterprise due diligence and compliance requirements.
    Top Skills: Compliance DocumentationKycRisk Assessment

    What you need to know about the Singapore Tech Scene

    The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

    Sign up now Access later

    Create Free Account

    Please log in or sign up to report this job.

    Create Free Account