Data Engineer

Responsibilities

• Build and maintain integrations that collect security data from third party platforms such as EDR tools, cloud services, and compliance systems
• Develop pipelines to parse, standardise, and normalise both structured and unstructured log data into a unified internal format
• Implement and manage log ingestion using tools such as Fluentd, Logstash, Vector, or similar collectors and forwarders
• Define and maintain mappings between external data schemas and internal data models to ensure consistency and usability
• Optimise ingestion workflows to improve performance, reliability, and data quality across all pipelines
• Produce clear technical documentation and support internal teams or customers with integration-related guidance
• Partner with backend and platform engineers to enable end-to-end data flow and contribute to automation initiatives, including AI-driven parsing capabilities

Your Skills

• 3–6 years of experience in data engineering, integration engineering, or security data pipelines
• Strong understanding of data integration concepts including ETL processes, API development, and schema design
• Hands-on experience parsing and transforming log data using regex, Grok patterns, or similar techniques across formats like JSON, syslog, or CSV
• Practical experience with log collection or forwarding technologies such as Fluent Bit, Logstash, Elastic Beats, OpenTelemetry, or equivalent tools
• Familiarity with security data platforms such as Splunk, Microsoft Sentinel, QRadar, or similar SIEM solutions
• Proficiency in at least one programming language such as Python, Go, or TypeScript
• Experience working in cloud environments (AWS, Azure, or GCP), with exposure to streaming or messaging systems like Kafka being advantageous