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Data Engineer Battery Jobs in Texas (NOW HIRING)

OrangePeople

Data & AI Solutions Architect

Plano, TX · On-site

This role is not a traditional delivery-focused data engineering position. The successful candidate ... Background in automotive, battery manufacturing, or industrial environments. Critical Success ...

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Data Engineer Battery information

What does a data engineer battery do?

A Data Engineer Battery specializes in designing, building, and maintaining data systems that support the collection, storage, and analysis of battery-related data. They work with large datasets from battery testing, manufacturing, and performance monitoring to ensure data quality and accessibility. Their role often involves developing data pipelines, integrating various data sources, and collaborating with data scientists and engineers to optimize battery technology and improve product performance. Data Engineer Battery professionals play a key role in advancing battery research and development by enabling data-driven insights.

What are the key skills and qualifications needed to thrive as a data engineer battery?

To thrive as a Data Engineer Battery, you need strong expertise in data modeling, ETL processes, and a background in computer science, engineering, or a related field. Familiarity with tools like SQL, Python, Spark, and cloud platforms such as AWS or Azure, along with experience in battery technology data systems, is typically required. Excellent problem-solving, communication, and teamwork skills help you collaborate with multidisciplinary teams and translate complex requirements into effective data solutions. These combined skills ensure that large-scale battery data is efficiently managed, enabling accurate analysis and supporting advancements in battery technology.

How does a data engineer battery typically collaborate with cross-functional teams?

As a Data Engineer in the battery industry, you will frequently work alongside data scientists, battery engineers, and product development teams to build and maintain data pipelines that collect, process, and analyze battery performance data. Collaboration is essential for aligning data infrastructure with the needs of R&D and operations, enabling accurate modeling and predictive analytics. You may also partner with IT and software development teams to ensure data quality, scalability, and security, ultimately supporting innovation and improved battery technologies.

What is the difference between Data Engineer Battery vs Data Engineer?

AspectData Engineer BatteryData Engineer
Required CredentialsBachelor's in CS, Data Science, or related field; certifications like AWS, GCP, or AzureBachelor's in CS, Data Science, or related field; certifications like AWS, GCP, or Azure
Work EnvironmentTech companies, battery manufacturing, automotive, energy sectorsTech companies, finance, healthcare, retail, and other industries
Employer & Industry UsageSpecialized in battery tech and energy storage industriesBroad industry application across various sectors

Data Engineer Battery focuses on data systems specific to battery technology and energy storage, while Data Engineer has a broader scope across multiple industries. Both roles require similar credentials and work environments but differ in industry specialization.

Are data engineers in demand?

Data engineers are in high demand across industries due to the increasing reliance on data infrastructure, cloud platforms, and big data tools like Hadoop and Spark. Organizations seek skilled professionals to build and maintain data pipelines, often requiring knowledge of programming languages such as Python or SQL, making this a strong job market for qualified candidates.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing need for data infrastructure, cloud computing, and big data processing. Skills in programming languages like Python and SQL, along with experience with tools such as Apache Spark and Hadoop, enhance job prospects in this field.

What are popular job titles related to Data Engineer Battery jobs in Texas?

For Data Engineer Battery jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Engineer Battery jobs in Texas look for?

The top searched job categories for Data Engineer Battery jobs in Texas are:

What cities in Texas are hiring for Data Engineer Battery jobs?

Cities in Texas with the most Data Engineer Battery job openings:

Data Engineer Battery jobs near you

Power Markets - Commercial Associate (Data Engineering Focus)

SaltHill Group

Houston, TX • On-site

$15.25 - $19.75/hr

Other

Posted 9 days ago

Key responsibilities

  • Establish and enhance data infrastructure and analytical tools to support commercial decision-making across various teams.

  • Design, build, and maintain scalable data pipelines and storage solutions using automated data feeds and APIs.

  • Develop and maintain processes and documentation to ensure data quality, consistency, and accessibility for the commercial organization.

Job description

A global Independent Power Producer (IPP) in Houston, operating a portfolio of thermal and renewable electricity generation and battery storage assets, is seeking a Commercial Analytics professional with strong data engineering and quantitative modeling capabilities. This newly created position will help build the data infrastructure and analytical tools needed to support commercial decision-making across Trading, Risk, Structuring, Asset Management, and Development.


Responsibilities include:

  • Establishing and enhancing the data infrastructure and commercial analytics capabilities needed to integrate real-time power and natural gas market information, asset and generation data, trading activity, weather, financial information, and other fundamental datasets to support commercial analysis, reporting, and decision-making.
  • Designing, building, and maintaining scalable data pipelines and storage solutions across various data integration methods, including APIs and other automated data feeds.
  • Developing and maintaining robust processes and documentation to ensure data quality, consistency, accessibility, and timely delivery across the commercial organization.
  • Collaborating and coordinating with key internal stakeholders, including Traders, Commercial Analysts, IT, Asset Management, and Development teams, to understand business requirements and efficiently onboard new datasets and analytical capabilities.
  • Supporting the development of advanced quantitative models, dashboards, and reporting tools for forecasting, pricing, portfolio risk management, scenario analysis, and asset optimization.
  • Translating complex market, portfolio, and asset data into actionable insights and analytical tools that support trading, origination, deal evaluation, risk mitigation, and asset performance optimization.


Education and Professional Requirements:

  • Bachelor’s degree required in Computer Science, Engineering, Mathematics, Statistics, Economics, Finance, Business, or another quantitative field. A Master’s degree is preferred.
  • Approximately 4+ years of experience in data engineering, data architecture, commercial analytics, quantitative modeling, or a related analytical role, preferably within wholesale power, energy, utilities, or commodity markets.
  • Ability to bridge technical data capabilities with commercial objectives and communicate effectively with quantitative, technical, and business stakeholders.
  • Experience working with energy market and commercial data, including exposure to power generation assets and technologies such as natural gas, wind, solar, and battery energy storage systems (BESS).
  • Ability to work with large and complex datasets and modern data warehousing, cloud, or scalable data infrastructure environments.
  • Experience developing and maintaining data integrations, pipelines, and storage solutions using APIs and other data transfer or automation methods.
  • Expertise in programming and data manipulation using tools such as Python, R, MATLAB, SQL, or similar technologies, along with experience developing reports and visualizations using Power BI, Tableau, or comparable platforms.
  • Strong analytical and quantitative problem-solving skills.
  • Familiarity with portfolio risk metrics and methodologies, including GMaR, VaR, and related measures.
  • Familiarity with power optimization and/or risk software such as PROMOD, PLEXOS, cQuant, or similar platforms is preferred.

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