Senior SIEM Data Engineer

Who we are looking for     We are looking   for a   Senior SIEM Data Engineer   reporting directly to the   Cyber Data Engineering Manager . You will lead th e design, onboarding, transformation, 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, designing scalable security telemetry pipelines, improving log fidelity and data quality, and ensuring reliable delivery of high-value 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 , complete, searchable, governed, and fit for purpose. As a senior engineer, you will also help define onboarding standards, mentor engineers, drive operational maturity, support complex troubleshooting, and contribute to the evolution of enterprise cyber data engineering capabilities.     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  Senior   SIEM Data Engineer   you will:   Design, build, and   ma intain   s calable SIEM and security telemetry pipelines across hybrid and multi-cloud environments.   Lead 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 onboarding requirements, expected fields, metadata, routing needs, retention considerations, and downstream SIEM/analytics use cases.   Build and   optimize   telemetry pipelines for parsing, filtering, masking, enrichment, normalization, event breaking, metadata tagging, and multi-destination routing.   Deliver reliable security telemetry to   Splunk, Databricks, and other SIEM or cyber analytics platforms .   Design and support Databricks data engineering patterns across raw, enriched, curated, and analytics-ready data layers.   Validate data quality across cyber data platforms for freshness, completeness, correctness, availability, timestamp accuracy, schema consistency, source attribution, routing accuracy, and latency.   Establish SIEM onboarding standards for source classification, source types, index routing, taxonomy alignment, metadata tagging, schema expectations, CIM/ECS alignment, and data quality controls.   Optimize   telemetry pipelines to reduce noise, control ingestion cost, improve performance, and preserve high -value security data for detection and investigation.   Lead troubleshooting of complex 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, escalation, and root cause analysis   for operational issues related to data engineering jobs, pipelines, ingestion failures, and issues leading to loss of data delivery to cyber data platforms.   Automate deployment, monitoring, alerting, validation, pipeline testing, repeatable onboarding, and operational support using CI/CD and infrastructure-as-code practices.