Lead Python Engineer

Overview

The Team S&P Global Energy’s Platform Engineering team is looking for an experienced Python/Spark data engineer. An ideal candidate will have a key role in accelerating the adoption and operational excellence of our Data Platform across the organization. This individual contributor will collaborate with platform users, data scientists, analysts, and product teams to deliver robust data solutions and drive best practices.

They should be comfortable handling new challenges involving emerging technologies. The candidate must follow best practices for software development and have experience building reusable and maintainable application code for future projects.

• Design and develop scalable data processing pipelines using Python and Apache Spark to handle large-scale energy datasets
• Build and maintain ETL workflows that transform raw energy market data into actionable insights for business stakeholders
• Collaborate with cross-functional teams to implement data solutions that support critical energy trading and analytics platforms
• Optimize data pipeline performance and ensure high availability of data processing systems serving global energy markets
• Contribute to the architecture and design of next-generation data infrastructure supporting S&P Global Energy's expanding portfolio
• Mentor junior engineers and participate in code reviews to maintain high engineering standards across the platform team
• Troubleshoot and resolve data pipeline issues in production environments, ensuring minimal downtime and data integrity
• Develop automated testing frameworks and monitoring solutions to proactively identify and prevent data processing failures

(This section is only applicable to US candidates) S&P Global states that the anticipated base salary range for this position is $100,000 to $150,000. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan.

This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please .

Basic

Required Qualifications:

• Bachelor's degree in computer science, Engineering, Data Science, or related technical field
• 6+ years of experience in data engineering with strong proficiency in Python programming and data manipulation libraries
• Hands-on experience with distributed computing frameworks such as Apache Spark, Databricks, Dask, or Ray for large-scale data processing
• Proven experience designing and implementing ETL/ELT pipelines using tools like Apache Airflow, Prefect, or similar workflow orchestration platforms
• Strong knowledge of database technologies, including both SQL databases (Postgre
  
  SQL, MySQL) and No
  
  SQL solutions (Mongo
  
  DB, Cassandra)
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform, including their data services and infrastructure components
• Strong analytical and problem-solving abilities with attention to detail in data quality and system reliability
• Excellent communication skills to collaborate effectively with cross-functional teams and translate technical concepts to business stakeholders
• Self-motivated with the ability to work independently while contributing to team objectives in a fast-paced environment

This is a hybrid-based opportunity, and is expected to be in the office 2-3 days/week.

We require all candidates who reach the final stage of our interview process to attend at least one in-person interview, which is ordinarily at your nearest S&P Global office. This must be completed before we can proceed to an offer.

At S&P Global Energy, our comprehensive view of global energy and commodities markets enables our customers to make superior decisions and create long-term, sustainable value. Our four core capabilities are:
Platts for news and pricing; CERA for research and…