Remote Battery Data Engineer: Predictive Pipelines

Plains VC; Tulsa (OK); Remote; USD 90,000 - 120,000; Full time

Job summary

Plains VC in Tulsa seeks a Data Engineer to build and maintain data infrastructure for battery optimization. You will analyze battery test and operational data and collaborate with R&D, manufacturing, and quality teams to drive process improvements and performance.

The role combines data science with engineering to model, predict, and optimize battery behavior under real-world conditions, including high-frequency sensor data, simulations, and real-time reporting.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Electrical/Chemical/Materials Engineering, Physics, or related field.
• Proficiency in programming (Python, SQL, related tools).
• Experience with machine learning and statistical modeling (regression, time series, anomaly detection).
• Experience handling experimental/test/multivariate data, including cleaning, preprocessing, and dealing with noise/missing data.
• Ability to quickly learn battery systems: cell/module/pack architectures, test protocols, degradation mechanisms, etc.
• Strong communication skills with the ability to translate technical results into actionable engineering insights.

Responsibilities

• Design, build, and maintain data pipelines and data stores (test data, manufacturing data, sensor data, etc.).
• Clean, preprocess, and validate large datasets from battery cycling tests, diagnostics, environmental tests, and field usage.
• Develop machine learning and statistical models to predict metrics such as SoC, SoH, degradation, thermal behavior, and safety events.
• Perform exploratory data analysis to identify patterns, anomalies, and correlations in battery performance.
• Collaborate with battery engineers, electrochemists, and manufacturing staff to define data requirements and design experiments.
• Implement monitoring tools, dashboards, and visualization to track battery health, production quality, and performance over time.
• Establish guidelines and best practices for data collection, versioning, quality assurance, and metadata management for battery datasets.
• Optimize data flows for computational efficiency and scalability, including high-frequency sensor data, large test datasets, and real-time streaming.
• Integrate battery system simulations and connect with physics-based models for predictive analysis.

Skills

Python

SQL

Machine learning

Statistics

Data cleaning

Education

Bachelor’s or Master’s in Data Science/CS/Engineering

Tools

AWS

Azure

GCP

Airflow

Spark

Job description

Plains VC in Tulsa seeks a Data Engineer to build and maintain data infrastructure for battery optimization. You will analyze battery test and operational data and collaborate with R&D, manufacturing, and quality teams to drive process improvements and performance.

The role combines data science with engineering to model, predict, and optimize battery behavior under real-world conditions, including high-frequency sensor data, simulations, and real-time reporting.