Data and Splunk Engineer - Officer at State Street in Bangalore

Job description

Job Description Data Engineer / Data Scientist/ Splunk Engineer , Officer Role Level Officer Role Type Individual Contributor Focus Area Data Engineering & Data Science Skill Mix 70% Data Engineering / Data Science; 30% Splunk Engineering Experience Target Approximately 10 years Who we are looking for The Data Engineer / Data Scientist/ Splunk Engineer , Officer, will support enterprise cybersecurity observability and analytics by combining deep Splunk engineering expertise with scalable data engineering and applied data science capabilities. The role is weighted (70%) towards Databricks-based data engineering, advanced analytics, and practical machine-learning solutions that convert complex security telemetry into reliable, actionable intelligence. The remaining focus(30%) towards Splunk engineering, with responsibility for developing searches, dashboards, alerts, data models, telemetry onboarding, and platform monitoring. What you will be responsible for As a Data Engineer / Data Scientist / Splunk Engineer , you will: · Design, develop, optimize, and maintain Splunk SPL searches, dashboards, reports, alerts, data models, field extractions, lookups, macros, and reusable knowledge objects. · Build and enhance security observability solutions across endpoint, web proxy, firewall, network, identity, cloud, vulnerability, threat intelligence, and other enterprise telemetry. · Onboard and validate new data sources, covering source analysis, parsing, normalization, timestamp validation, field mapping, data quality, and search readiness. · Troubleshoot ingestion failures, telemetry gaps, latency, duplication, parsing issues, search failures, and dashboard performance concerns. · Improve Splunk performance using efficient SPL, data model acceleration, summary indexing, lookup optimization, and appropriate search scheduling. · Develop proactive monitoring and alerting for Splunk platform health, ingestion volumes, search execution, dashboard availability, and operational service levels. · Partner with SOC, threat intelligence, detection engineering, security platform, and data teams to improve detection readiness and operational analytics. · Design and maintain scalable data ingestion and transformation pipelines using Python, SQL, PySpark, Databricks, Delta Lake, and cloud services. · Build curated, analytics-ready datasets with strong controls for data quality, reconciliation, lineage, observability, testing, and performance. · Integrate Splunk and Databricks workflows to support telemetry enrichment, historical analytics, aggregation, and downstream reporting. · Perform exploratory analysis and feature engineering to identify trends, anomalies, relationships, and risk indicators across cybersecurity datasets. · Develop or support practical statistical and machine-learning use cases including anomaly detection, classification, clustering, prioritization, and entity correlation. · Operationalize analytics through Git, CI/CD, automated testing, workflow orchestration, monitoring, documentation, and production support. · Create clear technical documentation, dashboard guides, data dictionaries, operational runbooks, and knowledge-sharing materials. · Mentor junior engineers, contribute to peer reviews, and promote reusable engineering and analytics practices. What we value These skills will help you succeed in this role: · Strong hands-on expertise in Splunk, including advanced SPL, dashboards, alerts, reports, data models, field extractions, lookups, macros, and performance optimization. · Experience with enterprise-scale log ingestion, security telemetry onboarding, data validation, troubleshooting, and operational monitoring. · Strong programming and data engineering skills using Python, SQL, PySpark, Databricks, ETL/ELT, Delta Lake, and distributed processing. · Understanding of Lakehouse architecture, data modeling, orchestration, data quality, reconciliation, lineage, observability, and pipeline optimization. · Practical knowled