ART 1468 - Data Engineer

FPT Software; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

FPT Software is seeking a seasoned data/software engineer to develop and maintain data pipelines and analytics workflows in a fast-moving environment. You will collaborate with data teams, automate deployment and monitoring, and optimize storage to boost performance across multiple platforms.

The role requires 5+ years of hands-on experience with Python, AWS, and Kubernetes, plus strong testing and DevOps practices. You will contribute to sprint planning and provide production support.

Qualifications

• Degree in Computer Science/Information Technology or related field.
• At least 5 years 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.

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

Data engineering

Unit & integration testing

Agile methodologies

DevOps practices

Communication

Education

Bachelor's degree in Computer Science/Information Technology or related fields

Tools

AWS

Kubernetes (K8s)

Snowflake

Databricks

Apache Spark

Apache Hive

Delta Lake / 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.