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Data Observability Engineer

  • Data Observability Engineer job type Posted on: Oct 14, 2026
  • Data Observability Engineer experience level Openkyber
  • Data Observability Engineer employment type Atlanta, Georgia
  • Data Observability Engineer employment type Onsite
  • Data Observability Engineer salary Full-time

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Job Title :

Data Observability Engineer

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

About the role: Looking for a Data Operations Engineer to support and optimize data infrastructure and pipeline operations across high-volume, distributed systems. This role focuses on ensuring reliability, scalability, and performance of data workflows while collaborating with engineering teams to maintain production-grade systems.

Key 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
Required Qualifications
  • 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
Preferred Qualifications
  • Experience with Elastic/ELK stack for logging and monitoring
  • Familiarity with Terraform for infrastructure as code
  • Experience with Kubernetes for container orchestration
What Success Looks Like
  • Reliable, efficient data pipeline operations with minimal downtime
  • Improved observability and monitoring of data systems
  • Timely resolution of production issues and performance bottlenecks
  • Well-documented systems and processes for maintainability
Work Environment

Fast-paced, engineering-driven culture Opportunity to work on modern data platforms and distributed systems

For applications and inquiries,

Jobcon Logo Position Details

Posted:

Oct 14, 2026

Reference Number:

89130-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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About the role: Looking for a Data Operations Engineer to support and optimize data infrastructure and pipeline operations across high-volume, distributed systems. This role focuses on ensuring reliability, scalability, and performance of data workflows while collaborating with engineering teams to maintain production-grade systems.

Key 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
Required Qualifications
  • 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
Preferred Qualifications
  • Experience with Elastic/ELK stack for logging and monitoring
  • Familiarity with Terraform for infrastructure as code
  • Experience with Kubernetes for container orchestration
What Success Looks Like
  • Reliable, efficient data pipeline operations with minimal downtime
  • Improved observability and monitoring of data systems
  • Timely resolution of production issues and performance bottlenecks
  • Well-documented systems and processes for maintainability
Work Environment

Fast-paced, engineering-driven culture Opportunity to work on modern data platforms and distributed systems

For applications and inquiries,

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