Джерело: CrawlJobs
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Principal Cybersecurity Data Engineer

Трудовий договір Повна зайнятість Гібридна робота

Дата публікації: 01.09.2026

Workday is a Fortune 500 company and a leading AI platform for managing people, money, and agents. As the Principal Cybersecurity Data Engineer, you will be the technical catalyst driving our transformation from a legacy data collection model into a mature, enterprise-grade Cybersecurity Data Organization. You will lead the Data Logistics vertical to architect the pipelines that power our next-generation security data lakehouse, scaling ingestion from a handful of data sources to 300+ complex, high-velocity security feeds and mentoring a globally distributed team.

Responsibilities

Design and implement ingestion, enrichment, and semantic layers for centralized data lakehouse; Redesign data onboarding and pipeline architecture to scale ingestion from legacy systems (Splunk) to modern lakehouse; Architect and deploy data observability, quality, and reliability frameworks from scratch; Serve as technical anchor for Data Logistics team and mentor engineers; Structure and model complex security data to enable advanced analytics, data science, and AI-driven security platforms

Requirements

Deep enterprise data engineering experience combined with strong understanding of cybersecurity operations; Understanding of security telemetry (EDR, network logs, threat intel) and challenges of migrating away from legacy SIEMs like Splunk; Understanding that security telemetry requires strict data isolation, chain-of-custody, and ultra-low latency; Ability to thrive in ambiguous, transformative environments and be comfortable architecting high-level strategy as well as diving into code; Expert-level hands-on experience designing and building cloud-native data lakehouses (e.g., Databricks, Snowflake, or native GCP/AWS data stacks); Ability to build semantic layers and optimize storage/compute for real-time streaming and historical analytics; High proficiency in Python, SQL, Scala, or Go; Deep experience with distributed data processing and orchestration tools (e.g., Apache Spark, Kafka, Airflow, dbt); Experience scaling ingestion to thousands of high-velocity sources; Hands-on experience designing and implementing data observability, automated quality checks, and reliability frameworks; Experience treating data infrastructure like code with CI/CD pipelines and version control; Ability to mentor engineers, instill modern software engineering practices, and guide team through technological and cultural shift

Benefits

Flex Work (hybrid flexible schedule); Workday Bonus Plan; role-specific commission/bonus; annual refresh stock grants; comprehensive benefits
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