A well-established energy trading firm in Houston is seeking a seasoned Python Data Engineer to expand its data assets and directly elevate its analytical and trading capabilities. In this role, you will sit at the intersection of engineering and the business — working shoulder-to-shoulder with traders, researchers, analysts, and data scientists to define requirements and deliver production-grade data solutions. You will own the design and implementation of modular, reusable data ingestion pipelines, ensuring code quality and architectural consistency across a centralized codebase. This is a high-impact individual contributor role for an engineer who thrives in a fast-paced, collaborative environment and wants their work to have a measurable effect on real trading decisions.
Key Responsibilities:
Interface directly with traders, analysts, researchers, and data scientists to gather, refine, and prioritize data requirements, translating complex business needs into functional, production-ready Python code.
Design, build, and maintain robust ETL and data ingestion pipelines using Python and Pandas, ensuring data accuracy, reliability, and performance at enterprise scale.
Write modular, reusable components for data interaction that conform to existing architecture patterns, coding conventions, and centralized codebase standards.
Coordinate efficiently with a globally distributed team of developers and business sponsors to deliver data solutions that span time zones and organizational boundaries.
Participate actively in the internal Python development community, acting as a technical liaison and working to standardize and consolidate core functionality within shared developer tooling.
Perform high-level technical troubleshooting across the data platform, diagnosing issues within a modular component architecture and driving them to resolution with minimal disruption to downstream consumers.
Requirements:
6 to 15 years of professional, enterprise-level Python development experience — candidates must be able to demonstrate a strong tenure record at one or a small number of employers.
Deep, hands-on proficiency with the Pandas library for data manipulation, transformation, and pipeline development in a production environment.
Proven experience building and maintaining ETL and data ingestion pipelines at enterprise scale, with a track record of delivering clean, well-architected code.
Background in financial trading, commodities, oil and gas, or a large banking/financial services firm — this domain context is essential for working effectively alongside trading and research teams.
Demonstrated ability to gather technical requirements directly from non-engineering stakeholders such as traders, analysts, and researchers, and translate those needs into reliable technical solutions.
Strong collaborative instincts and the communication skills to work across global development teams, contributing to shared codebases and upholding engineering standards.
Role Details:
Employment Type: Direct Hire
Location: Houston, Texas 77098
If you are a Python Data Engineer with deep financial or energy trading domain experience and a passion for building data infrastructure that drives real business decisions, we encourage you to apply.
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