Senior Software Engineer- Python, Data Engineer

Grade Level (for internal use): 10 You will be responsible for: Design and maintain optimal data pipeline architecture to ensure efficient, scalable, and reliable data flow across the organization. Assemble and integrate large, complex datasets that meet both functional and non-functional business requirements, ensuring data quality and consistency. Build and optimize infrastructure for extraction, transformation, and loading (ETL/ELT) of data from diverse sources using  SQL ,  Python ,  distributed data processing frameworks ,  cloud data platforms, and  cloud services  (such as  AWS, Azure, or GCP ). Collaborate with cross-functional stakeholders, including Executive, Product, Data, and Design teams, to address data-related technical challenges and support their data infrastructure needs. Develop data tools and frameworks for analytics and data science teams to empower them in building and optimizing products that position the company as an innovative industry leader. Partner with data and analytics experts to continuously enhance functionality, performance, and scalability of data systems. Lead project and stakeholder management activities, taking full ownership of the quality, timeliness, and successful delivery of data products and solutions. What We’re Looking For Technical Skills Minimum 5 years of experience in a data engineering role, with hands-on experience with  distributed data processing / big data frameworks (Databricks) ,  Python ,  cloud data platforms , and  AWS or other cloud environments  (e.g., Azure, GCP). Experience with  workflow orchestration / scheduling platforms Experience working with  version control systems  such as  GitHub, GitLab, Bitbucket, or Azure Repos . Experience maintaining and developing software in production environments utilizing CI/CD platforms  such as  Jenkins, GitLab CI, GitHub Actions, or Azure DevOps Experience with  modern Python API frameworks and strong understanding of RESTful services and good API design principles. Knowledge of system design concepts, including designing scalable, reliable, and fault-tolerant data architectures. Understanding of object-oriented programming principles and design patterns. Strong understanding of  big data / distributed systems technologies , including: streaming & messaging platforms   search & indexing / log analytics engines   structured & unstructured data container orchestration platforms   Demonstrated ability to design and implement end-to-end scalable and performant data pipelines. Proficiency in building data transformation processes, data structures, and workload management. Strong ability to manipulate and extract insights from large datasets using  SQL ,  Python , and  distributed processing frameworks Professional Skills: Strong analytical and problem-solving skills. Ability to collaborate and communicate effectively with both technical and non-technical stakeholders. Experience building solutions and working in Agile environments (e.g., Scrum, Kanban). About S&P Global Energy 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 advisory; Horizons for energy expansion and sustainability solutions; and Events for industry collaboration. S&P Global Energy is a division of S&P Global (NYSE: SPGI). S&P Global enables businesses, governments, and individuals with trusted data, expertise, and technology to make decisions with conviction. We are Advancing Essential Intelligence through world-leading benchmarks, data, and insights that customers need in order to plan confidently, act decisively, and thrive economically in a rapidly changing global landscape. Learn more at   www.spglobal.com/energy . What’s In It For You?

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