Factory Data Engineer
What you will be doing
As a Factory Data Engineer, you'll be the key bridge between raw factory data and functional models that deliver real business value. You’ll lead the ingestion, modeling, and visualization of industrial time-series data, transforming CSVs and historian formats into structured Factory Graphs and reporting dashboards. Your work will enable fast proof-of-value demos and provide the foundation for scalable customer solutions.
This role is ideal for engineers who thrive in fast-paced, collaborative startup environments, enjoy working end-to-end across the data pipeline, and can quickly turn ambiguity into actionable technical solutions.
Role responsibilities:
- Develop Python scripts or notebooks to convert raw data (e.g., CSVs, historian exports) into well-structured Parquet files for ingestion.
- Normalize and validate input data to ensure readiness for modeling.
- Develop scripts and/or notebooks to transform raw customer data files (CSVs and other historian formats) into properly formatted Parquet for ingestion by the data pipeline.
- Define v0 asset-based Factory Graph configurations aligned with the customer’s factory structure and connected to the ingested data tags.
- Define basic report definitions that render time-series charts of the most relevant data series, providing a “proof of life” for customers that we can ingest and understand their data
- Be able to deliver the above within 1-2 weeks of receiving sufficient customer data, or if the customer data is too complex or incomplete, raise that with the appropriate sales or technical team within that timeframe
- Throughout all these steps, partner closely with the domain-expert sales team to leverage their domain knowledge, identify key data/metrics, and incorporate them into the FactoryGraphs and demos you create. Additionally, work with the team to drive iterations with customers, collecting data / filling missing data gaps.
- Write clean, well-tested, scalable code and contribute to code reviews.
- Drive innovation and product impact through experimentation, critical thinking, and rapid iteration.
- Estimate and provide timely follow-up to assigned tasks or projects.
- Partner with stakeholders to gather requirements, prioritize tasks, and ensure alignment between business objectives and technical implementations.
- Analyze complex systems, hypothesize improvements, and test ideas across a broad technical surface area.
- Thrive in a startup environment: adaptable, autonomous, and outcome-driven.
- Bonus: extend those basic report definitions into customer-facing v0 demos that have a storyline illustrating key metrics/analyses and simple Vulcan queries.
This role is ideal for engineers who thrive in fast-paced, collaborative startup environments, enjoy working end-to-end across the data pipeline, and can quickly turn ambiguity into actionable technical solutions.
Role responsibilities:
- Develop Python scripts or notebooks to convert raw data (e.g., CSVs, historian exports) into well-structured Parquet files for ingestion.
- Normalize and validate input data to ensure readiness for modeling.
- Develop scripts and/or notebooks to transform raw customer data files (CSVs and other historian formats) into properly formatted Parquet for ingestion by the data pipeline.
- Define v0 asset-based Factory Graph configurations aligned with the customer’s factory structure and connected to the ingested data tags.
- Define basic report definitions that render time-series charts of the most relevant data series, providing a “proof of life” for customers that we can ingest and understand their data
- Be able to deliver the above within 1-2 weeks of receiving sufficient customer data, or if the customer data is too complex or incomplete, raise that with the appropriate sales or technical team within that timeframe
- Throughout all these steps, partner closely with the domain-expert sales team to leverage their domain knowledge, identify key data/metrics, and incorporate them into the FactoryGraphs and demos you create. Additionally, work with the team to drive iterations with customers, collecting data / filling missing data gaps.
- Write clean, well-tested, scalable code and contribute to code reviews.
- Drive innovation and product impact through experimentation, critical thinking, and rapid iteration.
- Estimate and provide timely follow-up to assigned tasks or projects.
- Partner with stakeholders to gather requirements, prioritize tasks, and ensure alignment between business objectives and technical implementations.
- Analyze complex systems, hypothesize improvements, and test ideas across a broad technical surface area.
- Thrive in a startup environment: adaptable, autonomous, and outcome-driven.
- Bonus: extend those basic report definitions into customer-facing v0 demos that have a storyline illustrating key metrics/analyses and simple Vulcan queries.