Senior Data Engineer
Built Technologies- Full Time
- Senior (5 to 8 years)
Candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, along with 3-5 years of experience in data engineering with a focus on Google Cloud Platform (GCP). They must have experience with Infrastructure as Code and provisioning infrastructure as code in a cloud environment, strong proficiency in Python and SQL, and experience with data modelling, Container platforms, ETL/ELT processes, and data warehousing. Familiarity with machine learning concepts and workflows is a plus.
The Data Engineer will be responsible for designing, developing, and maintaining scalable data pipelines using GCP services such as BigQuery, Cloud Run, and Google Cloud Storage. They will collaborate with AI engineers and data analysts to understand data requirements and deliver high-quality data solutions, implement data quality checks and monitoring, optimize data processing for efficiency, and contribute to the development of the overall data architecture and strategy. Additionally, they will design and implement infrastructure as code using tools like Terraform.
Provides financial information and analytics services
S&P Global provides financial information and analytics to a wide range of clients, including investors, corporations, and governments. The company offers services such as credit ratings, market intelligence, and indices, which help clients understand and navigate the global financial market. S&P Global's products work by utilizing advanced data analytics and research to deliver insights that assist clients in making informed decisions and managing risks. Unlike many competitors, S&P Global has a diverse range of divisions, including S&P Global Ratings and S&P Dow Jones Indices, which allows it to cater to various financial needs. The company's goal is to support clients in driving growth while also committing to corporate responsibility and positive societal impact.