Trách nhiệm chính

Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring timely and accurate delivery of data to stakeholders.
Work closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environments.
Develop and optimize large‑scale, batch, and real‑time data processing systems to enhance operational efficiency and meet business objectives.
Leverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring.
Utilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost‑efficiency.
Implement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflows.
Stay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions.

Yêu cầu công việc

Proficiency in Python for data processing and scripting (pandas, pyspark).
Experience with Apache Airflow for workflow automation.
Hands‑on experience with AWS services (Glue, S3, EC2, Lambda).
Experience working with Kubernetes and Docker for containerized environments.
Knowledge of columnar and big data databases (Athena, Redshift, Vertica, Hive/Hadoop).
Proficiency with version control systems such as Git.
Experience with CI/CD tools such as Jenkins, CircleCI, or AWS CodePipeline.

Yêu cầu ưu tiên

Familiarity with Langchain for building data applications involving natural language processing or conversational AI frameworks.
Experience with AWS SageMaker or Databricks for enabling machine learning environments.
Familiarity with both RDBMS (MySQL, PostgreSQL) and NoSQL (DynamoDB, Redis) databases.
Experience with enterprise BI tools like Tableau, Looker, or PowerBI.
Familiarity with distributed messaging systems such as Kafka or RabbitMQ for event streaming.
Experience with monitoring and log management tools such as the ELK stack or Datadog.
Knowledge of best practices for ensuring data privacy and security in large data infrastructures.
Banking domain experience is preferred, particularly exposure to digital banking, core banking, payments, or financial services projects.

Thông tin khác

The role is focused 75% on data engineering and 25% on supporting data science initiatives.
Location: Thành phố Hồ Chí Minh, Vietnam.
GFT Technologies is an AI‑centric global digital transformation company with over 12,000 technology experts operating in 20+ countries.
Application process: Due to high volume of applications, GFT may not respond to every candidate within 10 workdays.

Senior Data Engineer