Senior Data Scientist- Commercial Analytics.

About the position

Technical role focused on designing, building, and maintaining the infrastructure required for optimal extraction, transformation, and loading (ETL) of data from various sources. This position is responsible for ensuring the availability, reliability, and performance of data systems and supports trading analysts by providing clean and well-structured data for advanced analytics use cases. The Data Engineer will work closely with trading analysts and IT teams to ensure that data pipelines are robust, scalable, and aligned with business needs.

Responsibilities

• Design, build, and maintain efficient and scalable pipelines to support ingestion, transformation, and storage
• Develop and optimize ETL processes to ensure timely and accurate data availability for analytics and BI
• Implement data quality and validation processes to ensure the integrity and reliability of data
• Manage and monitor data systems to ensure high availability, reliability, and performance
• Maintain comprehensive documentation of data infrastructure, processes, and systems
• Troubleshoot and resolve data-related issues, ensuring minimal disruption to business operations
• Work closely with trading analysts and IT to understand data requirements and deliver solutions
• Provide support to trading analysts by ensuring they have access to clean, well-structured data
• Stay updated with the latest trends and technologies in data engineering and implement best practices to enhance data infrastructure
• Continuously evaluate and improve existing data pipelines and systems to increase efficiency and scalability
• Identify opportunities for automation and implement solutions to reduce manual data handling tasks

Requirements

• Extensive training in computer science, engineering, data science, or a related field
• 5+ years of relevant work experience in data engineering, data management, or a related role
• Strong proficiency in programming languages such as Python, SQL, and experience with data processing frameworks like Apache Spark or Hadoop
• Experience with cloud platforms such as AWS, Google Cloud, or Azure, and familiarity with data warehousing solutions like Snowflake or Redshift
• Excellent problem-solving skills and attention to detail, with a focus on data quality and reliability
• Strong communication and teamwork skills, with the ability to collaborate effectively with data scientists, analysts, and other stakeholders
• A keen interest in the energy trading sector and a commitment to staying updated with industry trends and developments