Risk Resources LLP hyd

Desired Competencies (Technical/Behavioral Competency)

• . Strong knowledge of Splunk architecture, components, and deployment models (standalone, distributed, or clustered)
• Hands-on experience with Splunk forwarders, search processing, and index clustering
• Proficiency in writing SPL (Search Processing Language) queries and creating dashboards
• Familiarity with Linux/Unix systems and basic scripting (e.g., Bash, Python)
• Understanding of networking concepts and protocols (TCP/IP, syslog)

Key Responsibilities

• Deploy Splunk Enterprise or Splunk Cloud on servers or virtual environments.
• Configure indexing and search head clusters for data collection and search functionalities.
• Deploy universal or heavy forwarders to collect data from various sources and send it to the Splunk environment
• Configure data inputs (e.g., syslogs, snmp, file monitoring) and outputs (e.g., storage, dashboards)
• Identify and onboard data sources such as logs, metrics, and events.
• Use regular expressions or predefined methods to extract fields from raw data
• Configure props.conf and transforms.conf for data parsing and enrichment.
• Create and manage indexes to organize and control data storage.
• Configure roles and users with appropriate permissions using role-based access control (RBAC).
• Integrate Splunk with external authentication systems like LDAP, SAML, or Active Directory
• Monitor user activities and changes to the Splunk environment
• Optimize Splunk for better search performance and resource utilization
• Regularly monitor the status of indexers, search heads, and forwarders
• Configure backups for configurations and indexed data
• Diagnose and resolve issues like data ingestion failures, search slowness, or system errors.
• Install and manage apps and add-ons from Splunkbase or custom-built solutions.
• Create python scripts for automation and advanced data processing.
• Integrate Splunk with ITSM tools (e.g., ServiceNow), monitoring tools, or CI/CD pipelines.
• Use Splunk's REST API for automation and custom integrations
• Good to have Splunk Core Certified Admin certification

Splunk Development and Administration

• Build and optimize complex SPL (Search Processing Language) queries for dashboards, reports, and alerts.
• Develop and manage Splunk apps and add-ons, including custom Python scripts for data ingestion and enrichment.
• Onboard and validate data sources in Splunk, ensuring proper parsing, indexing, and field extractions.

Key Responsibilities

- Develop front-end applications using React JS

- Design and implement back-end services using Node JS

- Collaborate with cross-functional teams to deliver projects

- Troubleshoot and optimize application performance

Requirements

- Strong experience with React JS and Node JS

- Proficiency in JavaScript, HTML/CSS, and relevant frameworks

- Experience with database management (e.g., MongoDB, PostgreSQL)

- Excellent problem-solving skills and attention to detail

• Please be specific with the required skill set while sourcing profiles. We require candidates with the following skills. Front end (jQuery, HTML5, Angular JS)+ Middleware (java 8 & Above, Spring boot)

Key Responsibilities :

- Centralize structured and unstructured data

- Contribute to data strategy through data modeling, management, and governance

- Build, optimize, and maintain data pipelines and management frameworks

- Collaborate with cross-functional teams to develop scalable data and AI-driven solutions

- Take ownership of projects from ideation to production

Ideal Qualifications and Skills :

- Bachelor's degree in Computer Science or equivalent experience

- 8+ years of industry experience

- Strong expertise in data modeling and management concepts

- Experience with Snowflake, data warehousing, and data pipelines

- Proficiency in Python or another programming language

- Excellent communication, collaboration, and ownership mindset

- Foundational knowledge of API development and integration

Nice to Have :

- Experience with Tableau, Alteryx

- Master data management implementation experience

Success Factors :

- Strong technical foundation

- Collaborative mindset

- Ability to navigate complex data challenges

- Ownership mindset and startup-like culture fit