Lightium Job Opportunity: Data Engineer/Scientist
Lightium is at the forefront of developing next-generation photonic integrated circuits on thin-film lithium niobate (TFLN). As we expand, we are seeking a Data Engineer/Scientist to analyze and visualize our technical data while contributing to the scaling of our infrastructure that transforms this data into valuable insights.
Position Summary
This hands-on role involves designing and implementing data pipelines, transformations, and analytical models that integrate our lab, manufacturing, and enterprise systems into a unified data platform. We are looking for a candidate proficient in writing production-level Python who can conceptualize data modeling and is enthusiastic about applying machine learning and AI tools to real-world scientific and operational challenges. Whether you're a recent graduate or an industry veteran eager to innovate at scale, this role is ideal for you.
Responsibilities
Data Engineering & Pipeline Development
- Design, build, and maintain scalable data pipelines ingesting data from lab instruments, PLM (Aras Innovator), ERP (Oracle NetSuite), MES, and other operational systems.
- Develop and manage ELT/ETL transformations using Python and DBT, applying software engineering best practices: version control, testing, modularity, and documentation.
- Utilize Apache Iceberg and cloud object storage (AWS S3 or GCP GCS) to create and manage a scalable data lake that supports both batch and incremental processing.
- Construct and operate distributed data processing workflows utilizing Apache Spark for large-scale transformation, aggregation, and feature engineering tasks.
- Implement data quality checks, schema validation, and pipeline monitoring to ensure data reliability, traceability, and usability.
- Manage and evolve the data warehouse layer, including table design, partitioning strategies, naming conventions, and access controls to support growing analytical workloads.
Data Modelling & Transformation
- Transform raw data from diverse sources into well-structured analytical datasets.
- Define and maintain DBT models implementing business logic, process metrics, and cross-system joins in a version-controlled, testable manner.
- Collaborate with domain experts to understand data semantics and ensure models reflect physical reality accurately.
- Document data lineage, transformation logic, and model definitions to foster trust and understanding among downstream users.
Dashboarding, Reporting & Manufacturing Visibility
- Design and develop dashboards providing real-time visibility into wafer yield, process control metrics, and device characterization trends.
- Create scheduled and on-demand reports delivering actionable insights without manual data wrangling.
- Build self-service data access tools and well-documented datasets for engineers to quickly find their answers.
- Work with teams to define key performance indicators (KPIs) and visualizations essential for daily decision-making.
- Continuously improve the reporting layer as new process steps and measurement types are introduced.
Manufacturing Analytics, Yield & Process Optimization
- Develop statistical models and machine learning pipelines focused on wafer-level yield analysis.
- Create process optimization models correlating upstream parameters with downstream performance.
- Build anomaly detection systems to identify out-of-control process conditions early.
- Iterate on models using Python and libraries such as scikit-learn or PyTorch.
- Stay updated with advancements in scientific machine learning and semiconductor analytics.
Collaboration & Documentation
- Work closely with the Head of Data and various teams to translate data needs into well-defined engineering tasks.
- Maintain comprehensive documentation of pipeline logic and model definitions.
- Communicate progress and findings effectively, contributing to a culture of transparency and knowledge sharing.
What You’ll Bring
Experience and Skills
- A degree in computer science, data science, statistics, physics, engineering, or a related quantitative field.
- Background in physical sciences, physics, photonics, or engineering.
- Proficiency in Python, writing clean, maintainable code in a shared codebase.
- Strong SQL skills, capable of complex queries and schema design.
- Familiarity with cloud data platforms (AWS or GCP) including object storage and cloud-native services.
- Experience with data warehousing, Apache Iceberg, and cloud object storage.
- Hands-on experience with data pipeline tools such as DBT or Dagster.
- Understanding of machine learning fundamentals with practical model training experience.
- Curiosity about LLMs and AI agents.
- A detail-oriented mindset, prioritizing data quality.
Startup Mentality
A results-driven mindset focused on innovation and problem-solving. Proactive in taking ownership and thriving on delivering tangible outcomes in a dynamic environment.
Communication
Excellent written and verbal communication skills are essential. Fluency in English is required.
What We Offer
- A competitive compensation and benefits package, including an employee stock option plan (ESOP) and generous vacation.
- An opportunity to lead initiatives in the rapidly growing field of photonics.
- A collaborative and innovative work culture where your contributions shape the future.
- The chance to join a motivated, young team, creating, growing, and honing your professional skills quickly.
Final Thoughts
If you are passionate about building new technology from the ground up and thrive in a collaborative, results-driven environment, we would love to hear from you.
Apply online using the form below.
Only applications matching the job profile will be considered.
Lightium is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.