DataOps Elasticsearch

As a Data Engineer, your role involves efficiently integrating and processing data sources within the ecosystem of our customer. This position offers an exciting opportunity to work in a dynamic environment and shape the future of our customer's data infrastructure.

Key Responsibilities:

Data Source Onboarding:

• Identify, assess, and assist data source owners in onboarding new data sources
• Develop and maintain efficient data pipelines for various log sources (platform, application, security, etc.)

Data Parsing and Transformation:

• Design and implement data parsing and transformation to ensure structured and accessible data
• Collaborate with security analysts and data owners to understand data requirements

Data Quality Assurance:

• Ensure compliance with proper data quality standards and processes
• Review data, monitor data pipelines, and resolve data quality-related issues

User Support:

• Assist internal stakeholders in effectively accessing and utilizing data
• Troubleshoot queries and provide technical support

• Provide guidance and create/maintain content, visualizations, dashboards, and reports on supported platforms

Documentation:

• Create and maintain configuration guides and standard operating proceduresy

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Proficiency in Linux operating systems (e.g., CentOS, Ubuntu, Red Hat).
• Experience with CI/CD, Ansible, and Gitlab.
• Minimum of 3 years of Elasticsearch experience, including Elastic Ingest and Logstash pipelines, and Kibana data visualization.
• Knowledge of Splunk is advantageous.
• Ability to model and process large datasets using SQL, KQL, and SPL.
• Relevant certifications or technology work experience (e.g., CompTIA Linux+, Red Hat, Elastic, Splunk, etc.) is a plus.

General Framework:

• Start: As soon as possible
• Duration: 12 month (long-term with possibility of extending)
• On-Site Requirement: 40% on-site in Zurich, 60% remote within Switzerland