Data Engineer

Plains VC; Tulsa (OK); A distancia; USD 90.000 - 120.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

SQL

Machine learning

Statistics

Data cleaning

Educación

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

Herramientas

AWS

Azure

GCP

Airflow

Spark

Descripción del empleo

Role Overview

The Data Engineer will help build and maintain data infrastructure, analyze battery test and operational data, and work closely with R&D, manufacturing, and quality teams to drive improvements in battery optimization, processes, and performance. This role combines data-driven and AI methods with engineering expertise to model, predict, and optimize battery behavior under real-world conditions.

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 state-of-charge (SoC), state-of-health (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

Qualifications and Education

Required

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 (cycling, impedance, thermal), degradation mechanisms, etc.

Strong communication skills with the ability to translate technical results into actionable engineering insights.

Preferred

Experience in battery development (test labs, battery manufacturing, or R&D).

Knowledge of electrochemistry, thermal properties, and aging mechanisms of cells.

Experience with hardware and sensors embedded in battery systems (data acquisition, signal conditioning).

Familiarity with cloud platforms (AWS, Azure, GCP), streaming data, and big-data infrastructure.

Experience designing dashboards, monitoring systems, and real-time reporting solutions.

Prior work with simulation and modeling tools (battery simulation, thermal models, finite element).

Experience building automated data capture pipelines from instruments and test equipment.

Ability to manipulate and analyze large datasets at scale, applying programming expertise to data handling.

Strong focus on predictive modeling, degradation mechanisms, and optimization.

Seniority/Levels

This role is open to candidates at multiple levels of experience. Consideration will be given to both early-career and experienced professionals with the required skills and interest listed above.

Location

Tulsa, Oklahoma | Global/Remote Options Available

Why Join Us

Be part of an innovative startup at the forefront of energy storage, combining materials science with data engineering.

Contribute directly to the development of sustainable, domestically produced energy solutions with global impact.

Work closely with world-class scientists, engineers, and industry leaders to shape the future of batteries.

Grow your career in a fast-paced environment where data-driven insights fuel breakthrough innovation.