Operations Systems Engineer

Who You Are

The Operations System Engineer plays a critical role in converting operational logic into intelligent, data-enabled systems that improve decision-making, execution, and scalability across the business. This role blends systems thinking, data engineering, and operational modeling to drive clarity and efficiency in how teams work and make decisions.

The ideal candidate combines practical delivery instincts with strong architectural judgment. They know that value comes not from overbuilding, but from delivering quickly and refining thoughtfully. Our team does not believe in disappearing for months to build theoretically perfect solutions that miss the mark. We co-develop with users, launch MVPs early, and quietly make them better, faster, and cheaper in the background. This role is for someone who values delivery over polish but obsesses over long-term scalability, modularity, and reusability once the foundation is sound.

This individual will partner closely with engineers, functional experts, and enterprise IT teams to deeply understand process logic, decision frameworks, and data flows. From there, they will architect and build models, tools, or software that are interpretable, maintainable, and tightly aligned to operational needs. They will also guide the broader team in selecting the right technical stack based on the complexity of the data and the intended use of the tool, whether for single-use analysis, repeatable planning, or production-grade execution.

Responsibilities and Duties  

• Develop a deep understanding of process logic, decision frameworks, and operating models across manufacturing and business functions.
• Work directly with domain experts to understand how decisions are made, and bring in the right data to structure models and tools that reflect that logic.
• Own the full lifecycle of models, tools, or software from MVP to scaled deployment. Build alongside stakeholders, demonstrate value early, and iteratively refine solutions into durable systems.
• Design with modularity and reusability in mind. Ensure that once a function is automated through logic and data, it becomes faster, cheaper, and easier to deploy in future factories or business contexts.
• Design with the customer in mind, but recognize that when building foundational systems, initial requirements are only a starting point. You are responsible for innovating beyond what is asked, exploring what is possible, and delivering solutions that anticipate future needs and not just the current ones.
• Refactor repeatable logic into clean, maintainable modules that significantly reduce development time for future projects.
• Prioritize business impact and clarity over abstraction. Deliver useful tools quickly, then scale them thoughtfully in the background.
• Guide the team in choosing the right technology stack and architecture based on the complexity of the data and the intent of the tool. Make clear decisions between building one-off solutions and creating mission-critical systems.
• Collaborate closely with enterprise data and IT teams to ensure infrastructure, data governance, and integrations align with system architecture.
• Apply automation and AI frameworks thoughtfully to recurring operational problems, such as supplier quoting, master data normalization, or document-based workflows. Prioritize transparency and explainability in all solutions.
• Maintain model repositories, data pipelines, and supporting code using best practices in version control, collaboration, and performance monitoring.
• Lead documentation, reviews, and improvement cycles to ensure all systems are scalable, reliable, and well-understood by the broader organization.

Knowledge and Skill Requirements 

• Bachelor’s degree in Industrial Engineering, Computer Science, Operations Research, or a related technical discipline.
• At least five years of experience in systems modeling, data engineering, or applied decision science.
• Demonstrated ability to build tools and models from early prototypes to modular, production-ready systems.
• Proficiency in Python and SQL with experience using Git and collaborative software development workflows.
• Hands-on experience with cloud data platforms such as Snowflake or similar.
• Strong communication and cross-functional collaboration skills.
• Comfort navigating ambiguity and applying structured, practical thinking to open-ended operational problems.
• Master’s degree in a technical or applied field preferred.
• Experience with optimization modeling, simulation frameworks, or automation systems.
• Familiarity with manufacturing systems including MES, ERP, and CMMS.
• Exposure to modern data engineering tools such as dbt, Prefect, Airflow, or containerized environments.

Physical Demands and Working Conditions

• Move long distances (such as from building to building) and be stationary for extended periods of time
• Operate a computer and other office equipment, such as a laptop, copier/printer, etc in a fixed location

The starting base pay for this role is between $143,000 and $181,000 at the time of posting. The actual base pay depends on many factors, such as education, experience, and skills. Base pay is only one part of Sila’s competitive Total Rewards package that can include benefits, perks, equity, and bonuses.  The base pay range is subject to change and may be modified in the future.
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