We are seeking a Senior Software Engineer / Architect to own the design, quality, and technical direction of the systems that transform production and laboratory instrument data into reliable, analyzable information. Working within a cross-functional team of mechanical engineers, physicists, and process engineers, you will provide the technical leadership for these systems — modernizing an established Python codebase and leading its evolution from a file-based system toward a robust, queryable, production-grade data platform. In parallel with building the new architecture, you will maintain and troubleshoot the existing ingestion pipeline by triaging parsing failures from production and metrology tools, handling data-entry edge cases, and using those real-world failure modes to inform a more resilient schema for the future. You will also work closely with process engineers to understand their analysis needs by building automated plotting scripts and custom visualization workflows that instantly turn database queries into actionable engineering plots. Working independently, you will set the engineering standards that keep the codebase clear, understandable, and maintainable, ensuring the systems you build can be confidently operated and extended by a small technical team.
Responsibilities
- Own the architecture and technical roadmap for the organization's process-data systems.
- Lead the modernization of an established Python codebase into a well-structured, tested, and maintainable system, preserving existing output behavior throughout the transition.
- Design and implement the migration from file-based outputs to a relational database supporting queries and analysis, including schema design, data integrity, and migrations.
- Design and implement deployment and operations, including containerization, CI/CD pipelines, and reliable release processes from source control to production.
- Design robust, automated data-processing pipelines.
- Establish and enforce engineering standards — code quality, testing, type safety, code review, and documentation.
- Collaborate with engineers and scientists, translate domain requirements into technical designs, and mentor team members as the software function grows.
- Collaborate directly with process engineers to capture data visualization requirements, developing automated scripts and templates to generate, export, and deliver custom plots on demand.
- Maintain and troubleshoot the existing Python ingestion pipeline for factory and metrology tool data, quickly resolving parser errors caused by tool edge cases or technician data-entry errors to ensure uninterrupted data availability.
Requirements
- Extensive professional software engineering experience (typically 7+ years), including architecture and technical ownership of data-centric systems.
- Strong proficiency in Python and modern software engineering practices.
- Experience with and effective use of AI-assisted development tools.
- Relational database expertise, including schema design, SQL, data integrity, and query optimization.
- Experience with deployment and operations, including containerization (for example, Docker), CI/CD, and general infrastructure and operations responsibilities.
- Strong testing discipline, including experience establishing testing practices.
- A strong commitment to code quality, clarity, and maintainability, and to making systems understandable to those who will maintain them.
- A track record of modernizing or replacing legacy systems under backward-compatibility constraints.
- Proven technical leadership and the ability to work independently and set technical direction within a multidisciplinary team.
- Excellent communication skills, including the ability to explain technical decisions to colleagues who are not software specialists.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Preferred qualifications
- Experience designing data pipelines, including extract, transform, and load (ETL) processes, and event-driven or message-based systems.
- Experience working independently: establishing and upholding sound software-engineering discipline (testing, code review, documentation) and instilling those practices within a team of professional engineers who are not primarily software developers.
- Familiarity with the Python data ecosystem (Pydantic, NumPy, pandas, matplotlib, seaborn).
- Exposure to scientific, laboratory, or manufacturing data.
- Proven experience writing custom data visualization scripts and automated plotting routines to support engineering, physical science, or manufacturing workflows.
- Practical experience debugging and maintaining legacy data ingestion scripts in a live operational or manufacturing environment.
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