This role is focused on building and maintaining the data pipelines and models that support a centralized data platform for global energy traders and analysts. The Data Engineer will write Python code to facilitate the movement of market and fundamental data to various consumers, including analysts and AI systems. This position offers the chance to work closely with senior engineers and directly engage with users to solve real-world problems, contributing to the platform's evolution and readiness for AI applications.

Key Responsibilities:

Develop and maintain robust data pipelines that ensure the timely delivery of accurate market and fundamental data to analysts and applications. Collaborate with senior engineers to establish best practices and design patterns across a polyglot technology stack. Migrate legacy data pipelines to a modern Prefect-based framework, ensuring minimal disruption to ongoing operations. Optimize data storage and exposure methods within a Snowflake warehouse to enhance data accessibility and performance.

Required Qualifications:

A minimum of 3 years of hands-on experience in data engineering, specifically in building and operating production data pipelines. Strong proficiency in Python, with a focus on writing clean, tested, and maintainable code. Deep understanding of SQL for modeling, querying, and performance tuning. Experience with Snowflake or a comparable cloud data warehouse. Familiarity with dbt, pipeline orchestration tools (Prefect preferred), and AWS data services.

Additional Details:

Location:

Houston, TX 77027 This opportunity allows you to build a platform career while directly impacting the data needs of energy traders. Join a collaborative team of engineers and analysts dedicated to solving real challenges in the energy sector. #11943 #LI-HN1