ART 1468 - Data Engineer

FPT Asia Pacific; Singapore; On-site; SGD 80,000 - 130,000; Full time

Job summary

FPT Asia Pacific is seeking a seasoned data/analytics engineer to design and maintain data pipelines and ETL/ELT workflows, enabling advanced search and retrieval capabilities. You will collaborate with data teams to automate deployment, monitoring, and optimize data storage while ensuring smooth sprint planning and timely delivery.

The role requires 5+ years in software or data engineering with Python, strong unit/integration testing, and experience with AWS, Kubernetes,

Qualifications

• Bachelor's degree or higher in Computer Science/Information Technology or related field.
• Minimum 5 years hands-on experience in software or data engineering with Python proficiency.
• Experience with unit and integration testing.
• Familiarity with DevOps practices and Agile methodologies.
• Experience with AWS and Kubernetes (K8s).
• Experience with data platforms such as Snowflake, Databricks, Spark, Hive, Delta Lake, Iceberg, and vector databases.
• Experience with orchestration tools such as Airflow, Dagster, Prefect, and Temporal.
• Familiarity with GitHub workflows and Datadog.
• Excellent written and verbal communication skills.
• Agile mindset and quick learner, able to adapt to changes.

Responsibilities

• Develop and maintain data pipelines and ETL/ELT/analytics engineering workflows to support advanced search and retrieval capabilities.
• Collaborate with data teams to understand requirements and automate deployment and monitoring.
• Optimize data storage and troubleshoot issues to enhance performance.
• Work closely with data engineers and relevant parties to ensure sprints are planned out properly and completed timely.
• Perform BAU monitoring, investigations and resolutions.
• Assist with data governance and data management initiatives.
• Production and application support from a day-to-day basis.

Skills

Python

Unit testing

Integration testing

DevOps practices

Agile methodologies

Communication skills

Education

Degree in Computer Science/Information Technology or related fields

Tools

AWS

Kubernetes

Snowflake

Databricks

Apache Spark

Apache Hive

Delta Lake

Apache Iceberg

Airflow

Dagster

Prefect

Temporal

GitHub workflows

Datadog

Job description

Key Responsibilities:

• Develop and maintain data pipelines and ETL/ELT/analytics engineering workflows to support advanced search and retrieval capabilities.
• Collaborate with data teams to understand requirements and automate deployment and monitoring.
• Optimize data storage and troubleshoot issues to enhance performance.
• Work closely with data engineers and relevant parties to ensure sprints are planned out properly and completed timely.
• Perform BAU monitoring, investigations and resolutions.
• Assist with data governance and data management initiatives.
• Production and application support from a day-to-day basis.

Skillset Requirements

• Possess a degree in Computer Science/Information Technology or related fields.
• At least 5 years of hands-on experience in software or data engineering with proficiency in Python.
• Strong experience in unit and integration testing.
• Familiarity with DevOps practices and Agile methodologies.
• Experience with AWS and Kubernetes (K8s).
• Familiarity with data platforms such as Snowflake, Databricks, Apache Spark, Apache Hive, open table formats (Delta Lake, Apache Iceberg), and vector databases.
• Experience with orchestration tools such as Apache Airflow, Dagster, Prefect, and Temporal.
• Familiarity with GitHub workflows and Datadog.
• Good written and verbal communication skills.
• Agile, fast learner and able to adapt to changes.