SIV Test Automation & Data Analytics Engineer

Our System Integration Validation (SIV) group leads the validation efforts for next-generation electro-optical devices and systems. NewPhotonics is revolutionizing data center processing with novel photonic engines that address power and performance challenges. We are looking for an SIV Test Automation Data Analytics Engineer to join our dynamic team. This role uniquely combines test automation with data engineering and analytics to drive product validation and characterization.

Responsibilities:

• Design and develop the test automation framework for product validation (CVT, DVT, FT, characterization), including architecture for test software and instrument drivers.
• Lead and implement automated test sequences for PIC-on-board and module-level validation, covering both CVT and DVT campaigns.
• Design and maintain the results database, including schema definitions for DUTs and test conditions, as well as APIs for data handling.
• Build analytics and reporting tools, such as scripts and dashboards, to track parametric distributions, yield, and trends.
• Integrate data from outsourced wafer-level, burn-in, and HTOL testing into the data model to enable comparison with bench data.
• Support internal reliability and qualification by preparing datasets for degradation and stress testing.
• Maintain test software quality through version control, code reviews, and regression testing.
• Provide user support to engineers and technicians utilizing the developed tools.
• Collaborate with other project teams, including HW, SW, Production, Photonics, and more.
  
  

• B.Sc. or M.Sc. in Electrical/Computer Engineering, Physics, Computer Science, or similar.
• 3+ years of experience in automated test development for hardware (RF, optics, mixed-signal, or similar).
• Hands-on experience with test environments such as NI LabVIEW/TestStand, Keysight PathWave, or Python-based frameworks for instrument control.
• Solid programming skills, particularly in Python.
• Experience controlling lab instruments (OSA, oscilloscopes, BERTs, VNAs, etc.) over standard interfaces like GPIB, LXI, or USB.
• Strong skills in data analysis and visualization using tools like Python, Jupyter, Pandas, or SQL.
• Experience with databases (SQL or NoSQL) and basic data engineering concepts.
  
  

• Knowledge of photonic integration technology and its ecosystem.
• Experience with test systems for optical transceivers or silicon photonics.
• Familiarity with software engineering best practices, such as unit tests, code style, and documentation.