Data Engineer
Coherent Corp.JobsCloseBy Editorial Insights
Coherent Corp seeks a Data Engineer for its Zurich Laser Business onsite. You will design and maintain data pipelines linking production equipment, operations systems, and business applications, ensuring data is accessible and reliable for R&D, production, and analytics. The role covers on-premises and cloud environments, focusing on Databricks, ETL, data integration, governance, and pipeline optimization. Ideal candidates hold a bachelor or master in CS or a related field with at least 1 year of hands-on experience, plus Python and SQL, SQL Server, data modeling, and Git; AWS or Azure and Airflow are a plus. Apply with CV and cover letter by Aug 18, 2026 to [email protected], highlighting cross-functional impact.
Coherent Corp. is the global leader in photonics, designing and manufacturing advanced laser, optical, and material technologies used by customers worldwide across industrial, communications, electronics, and instrumentation markets.
With a broad global footprint and deep engineering capability, we combine advanced manufacturing, applied innovation, and customer collaboration to deliver high-performance solutions that enable critical technologies and solve complex, real-world challenges.
About Coherent in Switzerland
Coherent Corp. Zurich is a key research and production hub specializing in advanced photonics, engineered materials, and high-power semiconductor laser technologies. Our teams develop and manufacture opto-electronic components and laser diodes for industrial, optical data transmission, life science, and high-precision applications, combining strong in-house R&D with state-of-the-art semiconductor manufacturing in an engineering-led culture.
Location: Zurich, Switzerland (Onsite) | Employment Type: Permanent, full-time
Job Summary
As a Data Engineer within our Laser Business Unit, you will develop, maintain, and improve the data pipelines that connect information from production equipment, operational systems, and business applications.
You will help make data accessible, reliable, and usable for teams across research and development, production, operations, data analytics, and other business functions. The role involves working across both on-premises and cloud-based environments, with a strong focus on practical data engineering, pipeline development, data integration, and Databricks.
Key Responsibilities:
- Develop and maintain scalable data pipelines to support data integration across on-premises and cloud environments.
- Implement and manage ETL processes, ensuring data accuracy and consistency through automated workflows.
- Integrate data from production equipment, operational systems, and other sources, making it accessible to teams across the business.
- Collaborate with cross-functional teams to support and optimize data storage solutions across on-premises and cloud environments.
- Use Databricks and related technologies for data processing and analytics activities.
- Monitor, troubleshoot, and optimize data pipelines to ensure performance, reliability, and scalability.
- Support data quality standards and data governance practices across platforms.
- Collaborate with data scientists, analysts, and stakeholders to support data-driven initiatives and provide technical guidance.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
Minimum 1+ years of hands-on data engineering experience in a production environment, ideally involving hybrid on-premises and cloud infrastructure.
Additional Skills and Requirements
Technical Skills
- Proficiency in Python and SQL for data manipulation and automation.
- Experience working with relational databases, such as Microsoft SQL Server.
- Understanding of data modelling, including schema design and normalization.
- Experience developing and managing data pipelines in a production environment.
- Experience with Databricks or a similar platform for scalable data processing and analytics.
- Knowledge of version control systems, particularly Git.
- Understanding of data quality and data governance principles.
Personal Skills
- Strong problem-solving skills and attention to detail.
- Clear communication with both technical and non-technical stakeholders.
- Collaborative approach and ability to work effectively across teams.
Additional Experience
The following would be advantageous:
- Experience with AWS or Azure, particularly within a hybrid on-premises and cloud environment.
- Familiarity with pipeline orchestration tools such as Apache Airflow.
- Experience with Apache Spark, CI/CD tools, data lakehouse architecture, or NoSQL databases.
- Background in the semiconductor or manufacturing industry.
Application Process
All candidates who wish to apply should submit a CV and cover letter outlining their interest in the position and how their skills and experience align with the requirements of the role.
Applications for this role close end of day on Tuesday, 18 August 2026.
If you require any adjustments or accommodations during the application process, please reach out to [email protected]. We are committed to creating an inclusive and accessible recruitment experience and encourage applications from individuals of all backgrounds.
Note to recruiters and employment agencies: We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.