Job Description

We are looking for a Senior Data Ops Engineer to manage, automate, and optimize data operations and data pipelines. The role will focus on ensuring the availability, quality, reliability, and performance of data platforms and workflows.

• Design, build, and maintain data pipelines and data workflows.
• Monitor data pipelines, jobs, and platforms to ensure reliability and availability.
• Automate data operations, deployments, monitoring, and operational processes.
• Troubleshoot data pipeline failures, data quality issues, and production incidents.
• Work closely with Data Engineering, Analytics, DevOps, and business teams.
• Implement data quality checks, validation, alerting, and monitoring.
• Manage data processing workflows across cloud and on-premise environments.
• Support CI/CD, version control, release management, and production deployments for data systems.
• Optimize pipeline performance, reliability, and operational costs.
• Maintain technical documentation, runbooks, and operational procedures.
• Participate in incident management, root-cause analysis, and continuous improvement.

• Strong experience with SQL, Python, and data pipeline technologies.
• Hands-on experience with ETL/ELT tools and workflow orchestration such as Airflow, Dagster, or equivalent.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Good understanding of databases, data warehouses, and data lakes.
• Experience with CI/CD, Git, Linux, scripting, and automation.
• Experience with monitoring, logging, alerting, and production support.
• Strong troubleshooting and problem-solving skills.
• Good understanding of data quality, governance, security, and operational best practices.

For applications and inquiries, contact:hirings@openkyber.com

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