Data Platform Engineer

ASTEK SINGAPORE INNOVATION TECHNOLOGY PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Astek Singapore Innovation Technology Pte. Ltd. is seeking an experienced Data Platform Engineer to build and operate data pipelines and analytics solutions for a scalable Data Warehouse environment.

You will collaborate with cross-functional teams to automate deployment, monitoring, and operational processes, while ensuring production stability and data quality through tests and governance initiatives.

Qualifications

• Degree in Computer Science or Information Technology or related field.
• At least 5 years of hands-on software or data engineering experience.
• Strong programming experience in Python and ETL.
• Experience with unit and integration testing.
• Experience with AWS and Kubernetes (K8s).
• Familiarity with Snowflake, Databricks, Spark, Hive, Delta Lake, Iceberg, Vector DBs.
• Experience with Airflow, Dagster, Prefect, or Temporal for orchestration.
• Familiarity with GitHub workflows, Datadog, DevOps, and Agile.
• Excellent analytical, troubleshooting, communication and collaboration skills.

Responsibilities

• Develop and maintain data pipelines, ETL/ELT processes, and analytics workflows.
• Collaborate with data/engineering teams to automate deployment, monitoring and ops.
• Optimise data storage, processing, and query performance; troubleshoot issues.
• Coordinate with data engineers and stakeholders to support sprint planning and delivery.
• Perform BAU monitoring, investigation, troubleshooting and incident resolution.
• Support data governance and data management initiatives.
• Provide day-to-day production and application support for platform stability.
• Develop and maintain unit and integration tests to ensure data quality.

Skills

Python

ETL

AWS

Kubernetes

Snowflake

Databricks

Apache Spark

Apache Hive

Delta Lake

Apache Iceberg

Vector databases

Airflow

Dagster

Prefect

Temporal

GitHub workflows

Datadog

DevOps practices

Agile methodologies

Analytical

Communication

Collaboration

Education

Degree in Computer Science or Information Technology

Tools

Airflow

Dagster

Prefect

Temporal

GitHub workflows

Datadog

Job description

Role Overview

We are looking for an experienced Data Platform Engineer to support the development and operations of Data Warehouse. The role will focus on building and maintaining scalable data pipelines, ETL/ELT workflows, data platforms, and analytics engineering solutions, while providing ongoing production and application support.

Key Responsibilities

• Develop and maintain data pipelines, ETL/ELT processes, and analytics engineering workflows to support advanced data search and retrieval.
• Collaborate with data and engineering teams to understand requirements and automate deployment, monitoring, and operational processes.
• Optimise data storage, processing, and query performance while troubleshooting technical issues.
• Coordinate with data engineers and stakeholders to support sprint planning and timely delivery.
• Perform BAU monitoring, investigation, troubleshooting, and incident resolution.
• Support data governance and data management initiatives.
• Provide day-to-day production and application support, ensuring platform stability and reliability.
• Develop and maintain unit and integration tests to ensure data and application quality.

Requirements

• Degree in Computer Science, Information Technology, or a related discipline.
• At least 5 years of hands-on Software Engineering or Data Engineering experience.
• Strong programming experience in Python and ETL
• Strong experience with unit and integration testing.
• Experience with AWS and Kubernetes (K8s).
• Familiarity with modern data platforms and technologies such as Snowflake, Databricks, Apache Spark, Apache Hive, Delta Lake, Apache Iceberg, and vector databases.
• Experience with workflow/orchestration technologies such as Apache Airflow, Dagster, Prefect, or Temporal.
• Familiarity with GitHub workflows, Datadog, DevOps practices, and Agile methodologies.
• Good analytical, troubleshooting, communication, and collaboration skills.

Key Technologies

Python | AWS | Kubernetes | Snowflake | Databricks | Apache Spark | Apache Hive | Delta Lake | Apache Iceberg | Vector Databases | Airflow | Dagster | Prefect | Temporal | GitHub | Datadog | ETL/ELT