Who we are looking for 

We are looking for a SIEM Data Engineer reporting directly to the Cyber Data Engineering Manager. You will support the onboarding, transformation, routing, validation, and operational support of cybersecurity telemetry and enterprise log data used for security monitoring, analytics, reporting, incident response, and cyber data science use cases. 

This role is focused on understanding diverse enterprise data sources, building and maintaining security telemetry pipelines, validating data quality, and ensuring reliable delivery of high-quality data into cyber data platforms such as Splunk, Databricks, and other SIEM or cyber analytics platforms. You will work closely with cybersecurity, infrastructure, cloud, application, and data engineering teams to ensure security telemetry is accurate, searchable, complete, and fit for purpose. 

Why This Role Is Important to Us 

The team you will be joining is part of Cyber Data & Analytics, a function that is vital to the company as it enables cybersecurity teams to make faster, data-driven decisions and strengthen the firm’s ability to detect, investigate, and respond to evolving cyber threats. 

High-quality cybersecurity data is foundational to effective threat detection, incident response, risk reporting, observability, automation, analytics, and compliance. This role helps ensure that enterprise security telemetry is properly onboarded, validated, enriched, routed, monitored, and continuously available to support critical cyber defense capabilities. 

What you will be responsible for 

As SIEM Data Engineer you will: 

• Support onboarding of security telemetry from applications, infrastructure, endpoints, identity platforms, network devices, cloud services, SaaS tools, databases, and security products. 

• Analyze source log formats and define ingestion requirements, expected fields, metadata, routing needs, and downstream SIEM/analytics use cases. 

• Configure telemetry pipelines for parsing, filtering, masking, enrichment, normalization, event breaking, metadata tagging, and destination routing. 

• Route security telemetry to Splunk, Databricks, and other SIEM or cyber analytics platforms. 

• Support validation and delivery of security telemetry into Databricks across raw, enriched, and curated data layers. 

• Support ingestion patterns such as syslog, HEC, REST APIs, cloud storage, streaming services, forwarders, and agent-based integrations. 

• Validate data quality in Splunk and Databricks for freshness, completeness, timestamp accuracy, field availability, schema consistency, source attribution, and routing accuracy. 

• Troubleshoot ingestion and data flow issues across sources, collectors, pipelines, SIEM platforms, Databricks tables, APIs, cloud storage, and streaming platforms. 

• Provide second-line-of-defense support for operational issues related to data engineering jobs, pipelines, ingestion failures, and issues leading to loss of data delivery to cyber data platforms. 

• Collaborate with Detection Engineering, Security Operations, Cyber Data Science, Observability, Cloud, Infrastructure, Application, and Platform teams to ensure telemetry supports security use cases. 

• Assist with source type assignment, index routing, taxonomy tagging, metadata enrichment, CIM alignment, schema mapping, and data validation. 

• Monitor pipeline health, dropped events, destination failures, ingestion latency, queue growth, and data delivery issues. 

• Document onboarding patterns, field mappings, transformation logic, routing decisions, data flow diagrams, runbooks, troubleshooting procedures, and operational handoffs. 

• Participate in production support, change management, incident response, root cause analysis, and continuous improvement activities 

• Second-line-of-defense support for operational issues related to data engineering (jobs/pipelines) and issues leading to loss of data delivery to Cyber data platforms 

What we value 

These skills will help you succeed in this role 

• Strong understanding of SIEM data onboarding, log ingestion, data routing, parsing, enrichment, validation, and troubleshooting. 

• Hands-on experience with Splunk or similar SIEM/log analytics platforms. 

• Hands-on experience or working knowledge of Cribl Stream or similar data pipeline technologies for routing, filtering, parsing, enrichment, transformation, and destination delivery. 

• Ability to understand and onboard telemetry from diverse enterprise data sources across cloud, endpoint, identity, network, application, infrastructure, database, SaaS, and security platforms. 

• Familiarity with common log formats such as JSON, XML, CSV, key-value, syslog, Windows Event Logs, cloud audit logs, API responses, and application logs. 

• Working knowledge of Databricks or similar analytics/lakehouse platforms is preferred. 

• Familiarity with Databricks data layers and data engineering concepts, including raw data ingestion, enrichment, curated tables, SQL-based validation, and analytics-ready datasets. 

• Ability to use SPL, SQL, Spark SQL, Python, Shell, or PowerShell for data validation, querying, troubleshooting, and automation. 

• Understanding data quality concepts, including log fidelity, event completeness, timestamp accuracy, field consistency, duplicate detection, routing validation, and data delivery monitoring. 

• Strong documentation, communication, collaboration, prioritization, and problem-solving skills. 

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Education & Preferred Qualifications 

• Master's or bachelor's degree in computer science, Cybersecurity, Information Technology, Engineering, Data Engineering, Data Analytics, Information Systems, or a related technical field; equivalent work experience may also be considered 

• 5+ years of experience in SIEM engineering, security data engineering, cybersecurity platform operations, or log analytics, with hands-on experience using Splunk or similar SIEM/log analytics platforms. 

• 2+ years of experience with Cribl Stream or similar data pipeline technologies such as Fluent Bit/Fluentd, Vector, Kafka, Syslog, HEC, REST APIs, or cloud-native ingestion services. 

• 2+ years of experience with Databricks, data lakehouse platforms, large-scale analytics platforms, or security data repositories for telemetry validation, analytics, and data engineering use cases. 

• Experience onboarding, validating, and troubleshooting security telemetry from diverse enterprise sources to support threat detection, observability, incident response, reporting, and cyber analytics use cases. 

• Experience querying and validating data using SPL, SQL, Spark SQL, Python, or similar languages. 

• Experience analyzing logs from cloud, endpoint, network, identity, infrastructure, application, database, SaaS, and security tools. 

• Experience with production support, issue troubleshooting, ticket documentation, root cause analysis, operational handoffs, and continuous service improvement. 

• Relevant certifications are preferred, including Cribl certifications such as Cribl Certified Observability Engineer, Splunk certifications such as Splunk Certified Admin, Splunk Certified Architect, or Splunk Certified Consultant, or equivalent hands-on platform experience. 

• Cloud, infrastructure, data engineering, or cybersecurity certifications are a plus. 

Work Requirement 

• This role may follow a hybrid work model, with in-office presence required based on team, business, and location expectations. 

• Standard working hours are 8:00 AM to 5:00 PM local time for the employee’s designated work location. Flexibility may be required for occasional operational support, release of activities, incident resolution, escalation support, or data delivery of recovery efforts.