Data Engineer
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Summary
Data Engineer in Singapore who builds and maintains data pipelines and ETL/ELT/analytics workflows supporting advanced search and retrieval, plus BAU monitoring, troubleshooting, and production support. Core stack: Python, AWS, Kubernetes, data platforms like Snowflake/Databricks/Spark, and orchestrators such as Airflow.
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:
Minimum 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.
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