
High-Performance Data Engineer
2 weeks ago
We are seeking an experienced data professional to design and build robust data pipelines. The ideal candidate will have a strong background in data engineering, with expertise in designing and implementing scalable ETL processes.
Main Responsibilities:
- Data Engineering & Pipeline Development:
- Design and implement high-performance ETL pipelines to ingest, transform, and load high-volume, high-velocity data from IT infrastructure, monitoring systems, and cloud environments.
- Develop batch and real-time data flows using frameworks such as Apache NiFi, Spark, Airflow, Flink, Kafka, and Talend.
- Optimize ETL jobs for scalability, fault tolerance, and low latency.
- Implement data validation, cleansing, and normalization processes for consistent AI model input.
- Integrate with AIOps platforms and ML pipelines using REST APIs or event-driven architectures.
- Develop and maintain robust data pipelines for ingesting, filtering, transforming, and loading data from various sources (e.g., network devices, appliances, databases, APIs, cloud storage).
- Application & Backend Development:
- Design and build backend services (microservices, APIs) in Python / Go/Java / Ruby to support data ingestion, metadata services, and configuration management.
- DevOps & Orchestration:
- Use tools like Elastic Stack, Apache Airflow, Prefect, or Dagster to schedule and monitor ETL jobs.
- Implement CI/CD pipelines for deploying ETL services and full-stack apps.
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