Intern - Data Engineering (Spring 2027, Jan to Jun)
At a glance
Junior Data Engineering role at SGX. Singapore, SG.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Find business questions that data science can address, then build solutions around the needs you identify
- Query warehouse data with kdb+ and q, then clean and reshape datasets in Python for modeling
- Train and test machine-learning models, tune their settings, and check results with suitable metrics
- Connect data, models and visualizations into production pipelines, using Kubeflow and Google Cloud services
- Support ongoing projects and system changes, and explain findings to business users through presentations and documentation
What you bring
- You are proficient in Python and SQL and understand modern AI and machine-learning methods
- You can handle large datasets, juggle multiple tasks and work well with a team
- You communicate clearly in English, both in writing and in conversation
- You are proactive and bring strong interpersonal skills
Who this fits
This is a junior internship running from January to June 2027. You’ll suit work that combines data preparation, modeling, cloud development and explaining technical results to business teams. A leave of absence may be needed to take the internship.
From the employer
SGX Group Internship Program
We are Asia’s leading and trusted securities and derivatives market infrastructure, operating equity, fixed income, currency and commodity markets to the highest regulatory standards. We also operate a multi-asset sustainability platform, SGX FIRST or Future in Reshaping Sustainability Together (sgx.com/first). We are committed to facilitating economic growth in a sustainable manner leveraging our roles as a key player in the ecosystem, a business, regulator and listed company. With climate action as a key priority, we aim to be a leading sustainable and transition financing and trading hub offering trusted, quality, end-to-end products and solutions. As Asia’s most international, multi-asset exchange, we provide listing, trading, clearing, settlement, depository and data services, with about 40% of listed companies and over 80% of listed bonds originating outside of Singapore. We are the world's most liquid international market for the benchmark equity indices of China, India, Japan and ASEAN. In foreign exchange, we are Asia's leading marketplace and most comprehensive service provider for global FX over-the-counter and futures participants. Headquartered in AAA rated Singapore, we are globally recognised for our risk management and clearing capabilities.
Be a part of this fast-paced world where your contributions count. SGX offers you the unique experience of gaining insights into the Exchange business and the finance value chain. You will be immersed in the respective specialist functions – at SGX, we believe that our interns are involved in real-time work from Day 1.
Note: Leave of Absence (LOA) may be required to take on the internship.
Data Engineering
Brief Overview:
As one of the key innovation drivers at Singapore Exchange, the Data & AI Engineering unit plays a pivotal role in shaping the future of data-driven solutions. We are at the forefront of emerging technologies such as Artificial Intelligence (AI), Generative AI (GenAI), Big Data, and Cloud Computing. Our responsibilities span across designing robust data and machine learning architectures, ensuring data integrity, developing data dictionaries and governance models, and building advanced analytics and visualization tools. These efforts aim to transform the organization and foster a strong data-driven culture.
Learning Outcomes
The Data & AI Engineering unit is seeking a Data Science Intern with a passion for exploring new technologies and innovative techniques. This internship offers an opportunity to challenge conventional thinking and develop creative solutions. The selected intern will gain hands-on experience with our suite of products and services, learn to build data science capabilities, and develop end-to-end production pipelines that deliver tangible business impact across multiple real-world use cases.
Job Description
- Identify business problems that can be addressed through data science and analytics.
- Propose and implement solutions to meet business needs.
- Learn to use kdb+ for extracting data from the data warehouse for modeling purposes.
- Gain experience in Google Cloud Platform (GCP) for cloud-based development.
- Build end-to-end production pipelines integrating data, models, and visualization/GUI to expose developed capabilities to business users.
- Support existing projects, platform migrations, and system improvements.
Technical responsibilities
- Data Extraction & Preparation:
- Use kdb+ and q language for querying large datasets from the data warehouse.
- Perform data cleaning and transformation using Python (pandas, NumPy etc).
- Feature Engineering & Modeling:
- Implement models using Python libraries such as scikit-learn, XGBoost, LightGBM, and TensorFlow/PyTorch for advanced ML.
- Experimentation & Optimization:
- Perform hyperparameter tuning with Optuna or scikit-learn GridSearchCV.
- Validate models using metrics libraries like scikit-learn metrics.
- Integrate visualization using matplotlib, Seaborn, Plotly, Dash, or Streamlit.
- Pipeline Development:
- Build end-to-end pipelines with Kubeflow.
- Tooling & Automation:
- Automate workflows using Python scripts, Shell scripting, and CI/CD tools.
- Cloud Development:
- Develop and deploy workflows on Google Cloud Platform (GCP) using services like BigQuery, Cloud Storage, and Vertex AI.
- Utilize Docker for containerization.
- Business Understanding & Presentation:
- Translate technical findings into actionable insights for business teams.
- Prepare clear and compelling presentations, ensuring non-technical stakeholders can easily understand the impact.
- Document workflows and results in Confluence.
Knowledge and Skills
Must-Have:
- Highly driven, proactive, and a strong team player.
- Excellent interpersonal skills with strong written and verbal communication in English.
- Ability to multitask effectively and manage large datasets.
- Solid understanding of modern AI/ML algorithms.
- Proficiency in Python and SQL.
Nice-to-Have (Advantageous):
- Experience with q/KDB+.
- Familiarity with Google Cloud Platform (GCP).
- Good understanding of financial markets.