Python / Data Engineer

Tech Aalto Pte ltd; Singapore; On-site; SGD 100,000 - 145,000; Part time

Job summary

Tech Aalto Pte Ltd in Singapore is seeking a Python/Data Engineer to support our Quantitative Investment team. You will build and optimize data pipelines, perform data manipulation with Python (Pandas/Polars) and DuckDB, and contribute to dataset quality for investment research.

You will collaborate with quants and researchers to translate investment requirements into robust analytic tools, validate ML models, and help implement backtesting and performance monitoring workflows in a fast-paced,

Qualifications

• A Bachelor's/Master's degree in CS, Data Science, Statistics or related field.
• 4–10 years hands-on Python programming with pandas/polars and DuckDB/SQL.
• Strong knowledge of statistics, probability and ML models.
• Experience with financial datasets and quantitative research is preferred.
• Familiarity with data visualization libraries (Matplotlib, Seaborn, Plotly).
• Understanding of data structures, algorithms and performance optimization.

Responsibilities

• Build, optimize and maintain data pipelines for quantitative strategies.
• Perform data manipulation and transformation using Python (Pandas/Polars/DuckDB).
• Collaborate with quants and researchers to provide datasets and tools.
• Support development and validation of statistical and ML models for investment decision-making.
• Ensure data quality and reliability across sources.
• Translate investment requirements into technical solutions.
• Automate data extraction, feature engineering and reporting tasks to improve research efficiency.
• Contribute to performance monitoring and backtesting frameworks for quantitative models.

Skills

Python programming

dataframes (Pandas/Polars)

statistics and ML concepts

communication skills

problem solving

Education

Bachelor’s/Master’s degree in CS/DS/Statistics/Math

Tools

Pandas

Polars

DuckDB

SQL

Matplotlib/Seaborn/Plotly

Job description

Python / Data Engineer – Quantitative Investment Support

Location: Onsite – Singapore

Employment Type: Contract

About the Role

We are looking for a highly skilled Python/Data Engineerwith strong experience indata manipulation, statistics, and machine learning modelsto support ourQuantitative Investment team. The ideal candidate should be comfortable working withdataframes, DuckDB (or similar technologies), and have a good foundation in quantitative analysis. This role involves building, maintaining, and optimizing data pipelines and providing analytical support for investment research.

Key Responsibilities

• Build, optimize, and maintaindata pipelines and workflowsfor quantitative investment strategies.
• Performdata manipulation, cleaning, and transformationusing Python (Pandas, Polars, DuckDB).
• Work closely withquantitative researchers and investment professionalsto provide high-quality datasets and analytical tools.
• Support the development and validation ofstatistical and ML modelsfor investment decision-making.
• Ensuredata quality, accuracy, and reliabilityacross multiple data sources.
• Collaborate with stakeholders totranslate investment requirements into technical solutions.
• Automate data extraction, feature engineering, and reporting tasks to improve research efficiency.
• Contribute toperformance monitoring and backtesting frameworksfor quantitative models.

Required Skills & Qualifications

• Bachelor’s/Master’s degree inComputer Science, Data Science, Statistics, Mathematics, or related field.
• 4–10years of hand‑on experience inPython programmingwith strong knowledge ofdataframes (Pandas/Polars)andDuckDB/SQL.
• Strong understanding ofstatistics, probability, and ML models(regression, classification, time series).
• Experience working withfinancial datasetsand supporting quantitative research is preferred.
• Familiarity withdata visualization libraries(Matplotlib, Seaborn, Plotly).
• Good understanding ofdata structures, algorithms, and performance optimization.
• Strong problem-solving and analytical skills.

• Exposure toquantitative finance, portfolio optimization, or risk modeling.
• Experience withcloud platforms (AWS/Azure/GCP)for data engineering.
• Familiarity withbig data technologies(Spark, Dask, PyArrow).
• Knowledge ofbacktesting frameworks and financial modeling tools.
• Experience inDevOps/CI-CD for data workflows.

• Ability to work in afast-paced, research-driven environment.
• Strong communication skills to collaborate withquants, data scientists, and portfolio managers.
• Detail-oriented with a focus ondata quality and reproducibility.