Data Analytics Engineer
Job Description
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)
If the role sounds of interest, feel free to reach out or apply below
Job Summary
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