Data Analytics Engineer

Data Analytics Engineer Splunk & Cribl SIEM Pipelines

We're hiring a Data Analytics Engineer to lead the migration, optimisation and secure operation of log ingestion and observability pipelines, with a focus on moving log sources from Splunk ingestion to Cribl Stream/Edge.

The role

• Lead the migration of log sources to load-balanced, fault-tolerant Cribl pipelines
• Design and run resilient pipelines for high ingest volumes (Cribl worker groups, external load balancers, syslog distribution)
• Onboard, parse and tune security log sources (firewalls, EDR, cloud, authentication, proxies), using data reduction to cut Splunk ingest and storage costs without losing security coverage
• Build and maintain Cribl and Splunk configs: transformations, field normalisation, masking, enrichment
• Work with SOC, IR and threat detection teams so security logs reach the SIEM reliably and are tuned for detection
• Monitor and resolve pipeline and SIEM issues, and report on ingest reduction, cost savings, pipeline health and event loss
• Document log flows, pipeline topology and operational procedures

What you'll bring

• Strong hands‑on Splunk SIEM engineering (indexers, search heads, clustering, forwarders, CIM, performance optimisation)
• 2+ years with Cribl Stream/Edge, including distributed, load-balanced deployments
• Solid grasp of log transport (syslog, HEC, TCP, UDP) and balancing strategies in HA logging environments
• Proven experience onboarding and tuning security log sources for SOC/IR support
• Advanced SPL, data models, event parsing and alert tuning
• Scripting skills (Python, shell/CLI or similar) for pipeline management and validation
• Good troubleshooting skills and experience building monitoring dashboards

Details

• 650 - 750 P/D
• Initial 6-month contract role (strong likelihood to extend)
• Hybrid role (2-3 days P/W on‑site)