Power Markets - Commercial Associate (Data Engineering Focus)

SaltHill Group Inc.
Houston, TX, United States
5 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
4 years minimum
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Business Analytics Applications Big Data Cloud Computing Computer Programming Data Architecture Data Transmissions Information Engineering Data Infrastructure Data Integration Data Warehousing R (Programming Language)
+11 more
Python (Programming Language) MATLAB Performance Tuning Power BI SQL Databases Tableau (Software) Technical Data Management Systems Data Processing Information Technology Tools for Reporting Data Pipelines

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., * 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.

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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