ETL & Data Engineer

2 weeks ago


Singapore Sagl Consulting Full time $80,000 - $120,000 per year

Role Overview:

ETL & Data Engineer to design, build, and maintain robust data pipelines and backend services that power AI-driven operations. The role involves working with high-volume IT and cloud data, optimizing ETL processes, and integrating with AIOps platforms and ML pipelines.

Key Responsibilities:

  • Build and maintain scalable ETL pipelines for batch and real-time data ingestion, transformation, and loading from diverse sources (IT infrastructure, cloud, monitoring systems, APIs).
  • Implement data validation, cleansing, and normalization for consistent AI model input.
  • Develop backend services and APIs to support data ingestion, metadata management, and configuration.
  • Optimize ETL jobs for performance, fault tolerance, and low latency.
  • Integrate with AIOps platforms and ML pipelines using REST APIs or event-driven architectures.
  • Schedule and monitor ETL workflows using tools like Airflow, Prefect, or Dagster.
    Support CI/CD pipelines for deploying ETL services and full-stack applications.

Required Skills & Tools:

  • Programming & Scripting: Python, Go (Golang), Java, Ruby, JavaScript/TypeScript )
  • ETL & Data Engineering: Apache NiFi, Spark, Airflow, Flink, Kafka, Talend
  • Orchestration: Airflow, Prefect, Dagster
  • Data Storage & Lakes: PostgreSQL, MongoDB, Elasticsearch, Snowflake, BigQuery, S3, GCS, Azure Blob
    Streaming Platforms: Kafka, Kinesis, Pub/Sub

Good to Have:

  • Experience with AIOps & Observability tools like Splunk, Dynatrace, AppDynamics, New Relic, Elastic Stack
  • Familiarity with ITSM systems (ServiceNow) and CMDB integrations
  • Understanding of metrics, logs, and traces for AI-driven operations


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