QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company’s next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future. About the team: The data engineering team at QuantumScape is small, agile, and central to the company's mission. We connect data from all manufacturing development areas to the engineers, analysts, and leaders who use it, enabling tighter feedback loops and driving clarity in decision-making. We achieve this by 1) improving access to data for both humans and AI agents, and 2) automating analytics to deliver actionable insights from our manufacturing development operations. What we need: As we expand to meet the demands of scaling our pilot line, you will be a critical new member with a high degree of impact. We are seeking a motivated data engineer who wants to help build our data product lifecycle from the ground up, accelerate our use of AI to augment engineering workflows, and directly contribute to the future of energy storage. What you’ll do: <ul><li>Design &amp; Build Data Pipelines: Design, build, and maintain robust, scalable ETL/ELT pipelines using Python and advanced SQL to process data from manufacturing systems, test hardware, and enterprise databases into our GCP/BigQuery data warehouse.</li><li>Manage the Data Product Lifecycle: Own new data products from end-to-end. You will collaborate with cross-functional stakeholders in Manufacturing, R&amp;D, and Quality to gather requirements, define data models, and deliver trusted, high-quality data solutions.</li><li>Enable Analytics &amp; BI: Develop and support analytics-ready datasets and interactive dashboards (e.g., using Plotly Dash) to report on production, yield, and key performance metrics for technical and executive audiences.</li><li>Ensure Data Quality &amp; Reliability: Implement automated testing, validation, and monitoring to ensure data integrity, identify opportunities for improvement, and uphold SLAs for your data products.</li><li>Automate &amp; Innovate: Serve as a key partner in our AI initiatives by preparing data for machine learning models focused on yield improvement, anomaly detection, and predictive analytics. Write reusable Python libraries to streamline common data analysis and automate engineering workflows.</li></ul> Skill you'll  need: <ul><li>A bachelor’s degree in a technical field (such as Computer Science, Physics, Mathematics, Engineering, or a related quantitative field) + 2 years of industry experience or a master’s degree in a technical field + 1 year of industry experience.</li><li>Fluency in Python and an advanced working knowledge of SQL for complex data transformation and analysis</li><li>Experience building, maintaining, and orchestrating ETL and ELT pipelines</li><li>Experience with a major cloud data platform and a modern data warehouse (GCP &amp; BigQuery preferred)</li><li>Experience using git and hosted services such as GitHub for version control, collaboration, and code review</li><li>Excellent problem-solving and communication skills for cross-functional collaboration</li><li>Excitement to work in a fast-paced, collaborative environment!</li></ul> Nice to have: <ul><li>Hands-on experience with “modern data stack” tooling for transformation (e.g., dbt) and orchestration (e.g., Prefect)</li><li>Comfort with various data models and/or experience with data warehouse design.</li><li>Hands-on experience with the Python Data Science stack (Pandas, NumPy, SciPy, scikit-learn).  </li><li>Hands-on experience with DevOps practices: CI/CD, infrastructure-as-code.</li><li>Hands-on experience building analytics dashboards using Plotly Dash.</li><li>Familiarity with manufacturing systems: Manufacturing Execution Systems (MES), SCADA, data acquisition, and product genealogy.  </li><li>Understanding of Statistical Process Control (SPC) concepts.</li></ul> Compensation &amp; Benefits: Expected salary range for this role is from $119,450 to $153,250, and a final salary will be determined by the candidate's experience and educational background. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits.We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation.

<h1>QuantumScape is a leader in the development of next generation solid-state lithium-metal batteries for use in electric vehicles. The company’s mission is to revolutionize energy storage to enable a sustainable future.</h1><iframe src="https://player.vimeo.com/video/466298136" width="640" height="360" frameborder="0" allowfullscreen="true"></iframe><h1>Join our team</h1>Do you want to help build one of the most critical parts of the future energy economy? Come join us on our mission as we revolutionize energy storage to enable a sustainable future.

Data Engineer

QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company’s next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future.&nbsp;About the team: The data engineering team at QuantumScape is small, agile, and central to the company's mission. We connect data from all manufacturing development areas to the engineers, analysts, and leaders who use it, enabling tighter feedback loops and driving clarity in decision-making. We achieve this by 1) improving access to data for both humans and AI agents, and 2) automating analytics to deliver actionable insights from our manufacturing development operations.&nbsp;What we need: As we expand to meet the demands of scaling our pilot line, you will be a critical new member with a high degree of impact. We are seeking a motivated data engineer who wants to help build our data product lifecycle from the ground up, accelerate our use of AI to augment engineering workflows, and directly contribute to the future of energy storage.&nbsp;What you’ll do:&nbsp;<ul><li>Design &amp; Build Data Pipelines: Design, build, and maintain robust, scalable ETL/ELT pipelines using Python and advanced SQL to process data from manufacturing systems, test hardware, and enterprise databases into our GCP/BigQuery data warehouse.</li><li>Manage the Data Product Lifecycle: Own new data products from end-to-end. You will collaborate with cross-functional stakeholders in Manufacturing, R&amp;D, and Quality to gather requirements, define data models, and deliver trusted, high-quality data solutions.</li><li>Enable Analytics &amp; BI: Develop and support analytics-ready datasets and interactive dashboards (e.g., using Plotly Dash) to report on production, yield, and key performance metrics for technical and executive audiences.</li><li>Ensure Data Quality &amp; Reliability: Implement automated testing, validation, and monitoring to ensure data integrity, identify opportunities for improvement, and uphold SLAs for your data products.</li><li>Automate &amp; Innovate: Serve as a key partner in our AI initiatives by preparing data for machine learning models focused on yield improvement, anomaly detection, and predictive analytics. Write reusable Python libraries to streamline common data analysis and automate engineering workflows.</li></ul>&nbsp;Skill you'll&nbsp; need:&nbsp;<ul><li>A bachelor’s degree in a technical field (such as Computer Science, Physics, Mathematics, Engineering, or a related quantitative field) + 2 years of industry experience or a master’s degree in a technical field + 1 year of industry experience.</li><li>Fluency in Python and an advanced working knowledge of SQL for complex data transformation and analysis</li><li>Experience building, maintaining, and orchestrating ETL and ELT pipelines</li><li>Experience with a major cloud data platform and a modern data warehouse (GCP &amp; BigQuery preferred)</li><li>Experience using git and hosted services such as GitHub for version control, collaboration, and code review</li><li>Excellent problem-solving and communication skills for cross-functional collaboration</li><li>Excitement to work in a fast-paced, collaborative environment!</li></ul>&nbsp;Nice to have:&nbsp;<ul><li>Hands-on experience with “modern data stack” tooling for transformation (e.g., dbt) and orchestration (e.g., Prefect)</li><li>Comfort with various data models and/or experience with data warehouse design.</li><li>Hands-on experience with the Python Data Science stack (Pandas, NumPy, SciPy, scikit-learn). &nbsp;</li><li>Hands-on experience with DevOps practices: CI/CD, infrastructure-as-code.</li><li>Hands-on experience building analytics dashboards using Plotly Dash.</li><li>Familiarity with manufacturing systems: Manufacturing Execution Systems (MES), SCADA, data acquisition, and product genealogy. &nbsp;</li><li>Understanding of Statistical Process Control (SPC) concepts.</li></ul>&nbsp;Compensation &amp; Benefits:&nbsp;Expected salary range for this role is from $119,450 to $153,250, and a final salary will be determined by the candidate's experience and educational background. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits.We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.&nbsp;We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation.

Data Engineer

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About the Company

QuantumScape

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