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Job description
We’re now expanding our data capabilities to meet the growing demands of a fast-paced, data-driven organisation. This role is a great opportunity for someone who’s eager to make an impact, get hands-on with modern tools, and help shape how we use data across our products and teams.
Design, develop, and maintain scalable data architectures and ETL pipelines, build and manage data models and data warehouse solutions, write clean, efficient Python and SQL code for data processing and transformation, integrate data from internal and third-party APIs and services, and optimise data pipelines for performance, scalability, and reliability.
Proven experience in data engineering and building scalable data solutions, strong collaboration skills, and a proactive, problem-solving mindset are required. Bonus points for experience with Airflow and/or dbt, experience working in Agile environments, and exposure to DevOps practices or CI/CD pipelines.
Company
Finance • Tech, Software & IT Services
S&P Global delivers trusted data, analytics, and intelligence that enable businesses, governments, and investors to make confident decisions across capital and commodities markets. Its core offerings include world-leading benchmarks, credit ratings, portfolio risk solutions, and ESG and sustainable finance metrics. The company supports clients through the energy transition, artificial intelligence acceleration, and evolving public and private markets, helping them uncover opportunities and mitigate risks. By combining deep expertise with advanced technology, S&P Global distinguishes itself as a vital partner for organizations navigating a rapidly changing global landscape.
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