Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Data Operation Engineer to build, maintain, and optimize scalable data pipelines and backend services. The role focuses on reliable data operations, large-scale data systems, containerized deployments, messaging integrations, monitoring, troubleshooting, and cross-functional collaboration.
Responsibilities
- Build, maintain, and optimize scalable data pipelines for high-throughput applications
- Support operational health of data systems, ensuring reliability and uptime
- Develop and enhance backend services using C# and Python
- Manage and query large datasets in Snowflake and Google BigQuery environments
- Deploy and maintain containerized applications using Docker in Linux-based systems
- Integrate and manage streaming/data messaging systems such as Kafka (Confluent) and RabbitMQ
- Monitor pipeline performance, troubleshoot issues, and implement improvements
- Collaborate with cross-functional teams to ensure smooth data operations and deployments
Skills
- 5+ years of experience in infrastructure and software engineering with exposure to data engineering and pipelines
- Proficiency in C# and Python
- Hands-on experience with Snowflake and/or Google BigQuery
- Strong experience working in Linux/Unix environments and Docker
- Experience building and maintaining data pipelines
- Familiarity with distributed messaging systems such as Confluent Kafka or RabbitMQ
- Ability to work independently in a remote environment while communicating effectively
- Experience with Elastic/ELK stack for logging and monitoring
- Familiarity with Terraform for infrastructure as code
- Experience with Kubernetes for container orchestration
Benefits
- Fully remote team with flexible collaboration
- Opportunity to work on modern data platforms and distributed systems
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