Senior Data Engineer

About Us

Founded in 2015 to develop the world’s first industrially scalable laser metal additive manufacturing solution, VulcanForms is reshaping how the world manufactures critical products. We build and operate advanced digital infrastructure that enables innovation, accelerates growth, and supports sustainability across aerospace, defense, medical, and other essential industries. Through our vertically integrated capabilities, including scalable additive manufacturing and precision machining, we deliver true end-to-end production at scale by combining cutting-edge technology with a foundation of proven industrial craftsmanship. Our team brings deep expertise in manufacturing, materials science, software, automation, and operations, united by a shared commitment to quality, curiosity, and accountability. We foster an inclusive culture where people take ownership, solve meaningful problems, and continuously learn, because we believe diverse perspectives lead to better outcomes.

Job Purpose

The Senior Data Engineer builds and maintains the data systems that power machine learning workflows, ensuring they scale effectively across VulcanForms. This role serves to provide the technical backbone of our Artificial Intelligence (AI) and data ecosystem—integrating data from factory systems, ensuring ML outputs are accessible and reliable, and delivering tools that enable Data Scientists, Machine Learning Engineers, and Application Engineers to effectively utilize data. By combining strong software engineering discipline, proficiency in data pipeline development, and understanding of ML production workflows, the Senior Data Engineer accelerates the adoption of AI-driven insights across the organization.

Key Responsibilities

- Improve the performance, reliability, and scalability of workflows running ML models and analytics to ensure rapid and accurate insights that support operational decision-making.

- Develop automated pipelines to collect, process, clean, and transform manufacturing data from a wide variety of equipment and sources into production-ready inputs.

- Own the processes for tracking, monitoring, and maintaining datasets and ML model versions in collaboration with Machine Learning Engineers and Data Scientists to ensure accuracy, reproducibility, and clarity.

- Partner closely with Systems Engineering, Software Engineering, Manufacturing, Quality, and Data Science teams to integrate their data capabilities into unified, robust analytics tools used across the factory.

- Implement automated monitoring, alerting, and validation of pipelines and models to ensure the continuous health of production AI systems.

- Serve as a technical resource for teams adopting AI tools, helping them understand data flows, troubleshooting issues, and suggesting improvements.

Qualifications

- Bachelor’s or master’s degree in computer science, Data Engineering, or a related field (or equivalent experience).

- 5+ years of experience in data engineering, ML infrastructure, or related software engineering roles.

- Strong proficiency in programming in Python and SQL.

- Strong proficiency in building data pipelines using tools such as Airflow, dbt, and Spark.

- Experience integrating and transforming data from complex systems (manufacturing, IoT, or industrial environments strongly preferred). · Experience processing and managing both tabular and unstructured data like images, video, and temporal data.

- Deep understanding of ETL/ELT best practices, workflow orchestration, and distributed data processing.

- Familiarity with deploying and maintaining ML models or data-driven applications in production.

- Strong software engineering fundamentals, including version control, testing, and CI/CD.

- Ability to independently own infrastructure components and collaborate across multiple technical teams.

Preferred Qualifications

- Experience with ML Ops frameworks or tools (MLflow, Kubeflow, SageMaker, etc.).

- Background working with real-time data, streaming architectures, or sensor/manufacturing data.

- Experience supporting AI/ML and Analytics development teams and deploying AI tools.

- Knowledge of data modeling, metadata management, and data governance.

- Familiarity with industrial data standards, equipment interfaces, or OPC/SCADA systems.

- Experience in manufacturing, hardware, or industrial environments.

- Experience driving large-scale data or ML infrastructure improvements across an organization.

VulcanForms offers a competitive salary and equity package. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, VulcanForms provides comprehensive benefits including medical, dental, vision, and life insurance; generous paid time off; and a 401(k) plan with company match.

The annual base salary range for this position is $125,000 to $170,000.