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Senior Associate (12 months contract), Investment Data Science (Data Engineer)
Location:
Singapore, SG,
Group: Portfolio Strategy & Risk Group
Department: Investment Data Science
Section: Investment Data Science
Job Type: Contract
Temasek is a global investment company headquartered in Singapore, with a net portfolio value of S$389 billion (US$288b, €267b, £228b, RMB2.08t) as at 31 March 2024.
Marking our unlisted assets to market would provide S$31 billion of value uplift and bring our mark to market net portfolio value to S$420 billion.
Our Purpose “So Every Generation Prospers ” guides us to make a difference for today’s and future generations.
Operating on commercial principles, we seek to deliver sustainable returns over the long term.
We have 13 offices in 9 countries around the world: Beijing, Hanoi, Mumbai, Shanghai, Shenzhen, and Singapore in Asia; and Brussels, London, Mexico City, New York, Paris, San Francisco, and Washington, DC outside Asia.
Temasek is looking to add a Data Engineer to work closely with other members of the Investment Data Science team to build, deploy and manage the data and analytics workflows used in our data-driven investment analysis process.
Responsibilities
- Build tools and automation capabilities for data pipelines that improve the efficiency, quality and resiliency of our data analytics platform
- Partner with the investment professionals, quantitative researchers, and data scientists to design, develop and deploy solutions that answer fundamental questions about companies, sectors, countries and financial markets
- Explore new external data sources to understand availability and quality =
- Develop solutions that enable investment professionals and data science teams to efficiently extract insights from data.
This includes owning the ingestion and transformation
Requirements
- Bachelor’s Degree in Computer Science, Information Technology, Computer Engineering, and/or related fields
- Passion for working with data and developing software to solve data processing challenges
- Proficiency with building, tuning, and debugging ETL pipelines in Python , including common libraries (Pandas, Numpy), and testing frameworks (e.g. PyTest)
- Experience working with SQL and relational databases, Snowflake is strongly preferred.
- Experience working with or managing cloud technologies e.g. AWS, Kubernetes.
- Experience with Data Warehousing and Machine Learning workflows
- Experience with CI/CD workflows preferred
- Experience with containerized services
- Strong written and verbal communications skills
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