Job Title

Splunk Data Administrator (Mid–Senior) – CIM / Data Onboarding / Hybrid

Architecture

Role Summary

We are seeking a mid to senior Splunk Data Administrator to own and continuously

improve Splunk data onboarding, normalization, and quality across a complex hybrid

Splunk environment (onprem and cloud).

The ideal candidate is hands-on with CIM alignment, data source onboarding, field

extractions (regex/props/transforms/ingest actions), TA deployment, and end-to-end

operational management of Splunk data pipelines.

You will act as the key point of contact for ensuring log sources are onboarded

correctly, parsed and normalized consistently, and made usable for security/IT

operations, dashboards, correlation searches, and reporting.

Key Responsibilities

Data Onboarding & Lifecycle Management

• Lead onboarding of new log sources end-to-end: requirements gathering, source

validation, parsing strategy, TA selection/deployment, CIM alignment, testing, and

release.

• Partner with Security/IT teams to translate use-cases into data requirements,

ensuring sources deliver the right fidelity, timeliness, and coverage.

• Manage onboarding at scale using best practices for source types, metadata

strategy, index & sourcetype governance, and naming conventions.

• Define and enforce data quality standards (field completeness, timestamps, event

consistency, parsing accuracy, duplication control).

CIM Normalization & Data Modelling

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• Normalize data to Splunk Common Information Model (CIM) with strong

understanding of data models (e.g., Authentication, Network Traffic, Endpoint,

Change, etc.).

• Ensure fields are aligned to CIM requirements to support Splunk Enterprise

Security (ES) and other CIM-based content.

• Validate normalization using SPL and develop reusable onboarding checklists.

Field Extraction, Parsing & Enrichment

• Design and implement robust field extractions using:

- props.conf / transforms.conf,



REPORT/TRANSFORMS stanzas

- regex and structured parsing (KV_MODE, JSON, XML)

- ingest-time vs search-time extraction strategy

- sourcetype / timestamp / line breaking configuration

• Implement enrichment and routing using event breaking, host/source normalization,

lookups, and tagging.

• Troubleshoot parsing issues (timestamp drift, multi-line events, encoding,

truncation, duplicate ingestion, broken extractions).

TA Installation & Configuration (Complex / Hybrid)

• Install, configure, and maintain Splunk Add-ons (TAs) and apps across:

- Heavy Forwarders / Universal Forwarders

- Indexers / Search Heads / SHC

- Deployment Server / Cluster Manager (where applicable)

• Maintain version compatibility and upgrade strategies for:

- Splunk Enterprise / Splunk Cloud

- Add-ons, apps, and content packs

• Package and deploy TAs using deployment pipelines and change management

controls.

• Ensure fields are aligned to CIM requirements

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Hybrid Splunk Architecture Operations

• Operate and support Splunk in complex environments:

- On-prem Indexer Cluster, Search Head Cluster, Forwarder tiers

- Splunk Cloud integrations where applicable (e.g., Heavy Forwarder, VPN,

PrivateLink, data forwarding patterns)

• Configure and troubleshoot data ingestion pipelines:

- Syslog (UDP/TCP), API-based collection, HEC, file monitors, Windows Event Logs,

cloud sources

• Ensure performance and reliability across the pipeline, including indexing

throughput, parsing overhead, and search impact.

Monitoring,



Troubleshooting & Governance

• Monitor ingestion health and pipeline performance:

- Forwarder health, queue saturation, parsing/indexing delays, dropped events

• Maintain governance for indexes, sourcetypes, retention, RBAC and data access

boundaries (as required).

• Contribute to operational runbooks, SOPs, and documentation; drive continuous

improvement in onboarding and normalization standards.

Required Skills & Experience (Mid–Senior)

• 5–10 years experience with Splunk administration and data onboarding (or

equivalent depth).

• Robust practical knowledge of:

- CIM normalization, tags/eventtypes, datamodel alignment

- Field extraction (regex, JSON/KV extraction), and troubleshooting parsing issues

- props.conf / transforms.conf, sourcetypes, timestamps, line-breaking

- TA installation/configuration and deployment patterns across Splunk tiers

Public

• Experience with complex Splunk architectures:

- Indexer clusters, SH/SHC, forwarder management, deployment server

- Hybrid patterns (on-prem + cloud), connectivity, and ingestion strategies

• Comfortable writing and validating SPL for data quality and CIM compliance.

• Strong log source knowledge across common domains:

- Security: EDR, firewall, proxy, IAM/auth, VPN, email security

- Infrastructure: Windows, Linux, network devices, virtualization

- Cloud: AWS/Azure/GCP logging patterns (nice-to-have)

Preferred / Nice-to-Have

• Experience with Splunk Enterprise Security (ES) and ES add-ons / CIM compliance

expectations.

• Knowledge of Splunk Ingest Actions / Edge Processor (or modern ingestion tools,

where applicable).

• Familiarity with:

- HEC, API ingestion, message queues

- ITSI / Observability (bonus)

• Splunk certifications (preferred):

- Splunk Core Certified Power User / Admin

- Splunk Enterprise Certified Admin

- Splunk ES Admin (bonus)

📌 Splunk Data Administrator (Melbourne)
🏢 Wipro APAC
📍 Melbourne