Data Engineer Statistica/ ML Model

TECH AALTO PTE. LTD.; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

A data technology company in Singapore is seeking a Data Engineer skilled in statistical and machine learning models. You will design and maintain data pipelines, collaborate with data science teams, and ensure efficient workflows for data preparation. The ideal candidate has a degree in a related field and 4–15 years of experience. This full-time role offers opportunities to work with cutting-edge tools in a dynamic environment.

Qualifications

• 4–15 years of experience as a Data Engineer.
• Experience with machine learning workflows.
• Experience working in a quantitative, trading, or data-driven environment is advantageous.

Responsibilities

• Design, build, and maintain scalable data pipelines to support ML and statistical modeling.
• Integrate structured and unstructured data from multiple sources into analytical environments.
• Implement efficient ETL/ELT workflows for data preparation, cleaning, and feature engineering.
• Collaborate with data science teams for deployment of ML models.
• Optimize data workflows for performance, scalability, and reliability.
• Manage data quality, lineage, and governance standards.

Skills

Python

SQL

Data manipulation frameworks (Pandas, PySpark, DuckDB)

ML model lifecycle

Data pipeline tools (Airflow, Prefect, dbt)

Cloud platforms (AWS, Azure, GCP)

Containerization (Docker)

CI/CD pipelines

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field

Job description

Job Title: Data Engineer – Statistical/ML Models

Location: Singapore
Experience: 4–15 years
Employment Type: Full-time

About the Role:

We are looking for a Data Engineer experienced in building and managing data pipelines for statistical and machine learning models. The role involves close collaboration with data scientists and analysts to enable scalable model training, data ingestion, and real-time analytics.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines to support ML and statistical modeling.
• Integrate structured and unstructured data from multiple sources into analytical environments.
• Implement efficient ETL/ELT workflows for data preparation, cleaning, and feature engineering.
• Collaborate with data science teams to ensure smooth deployment of ML models to production.
• Optimize data workflows for performance, scalability, and reliability.
• Manage data quality, lineage, and governance standards.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 4–15 years of experience as a Data Engineer with exposure to machine learning workflows.
• Strong proficiency in Python and SQL; experience with data manipulation frameworks (Pandas, PySpark, DuckDB).
• Familiarity with ML model lifecycle, from data preprocessing to deployment.
• Experience with data pipeline tools (Airflow, Prefect, dbt) and cloud platforms (AWS, Azure, GCP).
• Knowledge of containerization (Docker) and CI/CD pipelines.
• Experience working in a quantitative, trading, or data-driven environment is advantageous.

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