Senior Cybersecurity Data Engineer - Data Platform & Lakehouse SME
About The Position
Workday is seeking a Senior Data Engineer to serve as the subject matter expert for Data Platform and Lakehouse Architecture on its newly formed Cybersecurity Data Engineering & Enablement Team. The team is building a centralized, cloud-native security data lakehouse to unify enterprise security telemetry and provide trusted intelligence for threat hunters, data scientists, and incident responders. The role focuses on building, securing, and optimizing the AWS-based data lake, storage layers, and compute infrastructure that underpin security operations. The SME will define how data is stored, partitioned, and accessed, and establish frameworks, compliance guardrails, and compute engine standards that let data engineering and AI/ML teams build workloads securely and at scale. The position is based on Workday’s flexible-work approach, which combines in-person and remote work. Teams spend at least half of their time each quarter in an office or in the field with customers, prospects, or partners, with flexibility to shape schedules around business, team, and personal needs. The position may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants.
Requirements
- At least 7 years of experience in data platform engineering, cloud infrastructure engineering, or data architecture supporting large-scale enterprise data lakes.
- At least 3 years operating Apache Iceberg (highly preferred) or Delta Lake in production, with expert understanding of file-format internals such as Parquet, ORC, and metadata layers.
- At least 3 years of production-level experience with AWS data infrastructure, specifically AWS EMR (including Spark/Presto/Trino tuning), AWS Athena, S3 infrastructure, and AWS Lake Formation.
- At least 3 years using Terraform or AWS CDK to provision secure, multi-environment data infrastructures.
- At least 3 years of experience with modern cloud data warehouses such as Snowflake, Databricks, or AWS Redshift, including cluster sizing and workload management.
- Advanced proficiency in SQL, including performance tuning and query optimization.
- Proficiency in Python or Bash for infrastructure automation.
Nice To Haves
- AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer certification.
- Experience setting up multi-region data lakes, cross-account data sharing, or data mesh architectures.
- Experience with open-source query engines such as Trino or StarRocks.
Responsibilities
- Lead the design, infrastructure implementation, and evolution of the enterprise AWS Data Lake/Lakehouse ecosystem.
- Define standards for open-table formats such as Apache Iceberg or Delta Lake, including partition strategies, schema evolution, file compaction, retention, and storage tiering.
- Design, configure, and maintain foundational compute engines and query layers, including AWS EMR, AWS Athena, and Redshift.
- Define foundational infrastructure and access patterns for enterprise Data Marts, optimizing underlying engines for heavy, concurrent queries from BI and reporting tools.
- Architect and enforce data governance, network isolation, encryption at rest and in transit, and fine-grained access controls using AWS Lake Formation and AWS IAM.
- Provision, deploy, and version-control the data platform using automated, reproducible infrastructure-as-code.
- Monitor and optimize AWS data spend, and perform capacity planning to accommodate data-volume growth.
Benefits
- May be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
- May be eligible for annual refresh stock grants.
- Flexible work approach combining in-person and remote work.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
