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 Cybersecurity Data Engineering & Enablement Team. The team is building a centralized, cloud-native security data lakehouse to unify enterprise security telemetry and support threat hunters, data scientists, and incident responders with trusted, timely intelligence. The role is responsible for architecting, building, securing, and optimizing the platform’s data lake, storage layers, and compute infrastructure. The SME will define how data is stored, partitioned, and accessed, and establish the frameworks, compliance guardrails, and compute standards that enable downstream Data Logistics and AI/ML teams to deliver workloads securely and at scale. The role also covers enterprise data marts and the infrastructure and access patterns supporting BI and reporting workloads.
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 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 the AWS data stack, specifically AWS EMR (including Spark/Presto/Trino tuning), Athena, S3 infrastructure, and 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
- Apache Iceberg production experience is highly preferred over Delta Lake.
- AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer certification.
- Experience establishing 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, implementation, and evolution of the enterprise AWS Data Lake/Lakehouse ecosystem.
- Set standards for open-table formats, partitioning, schema evolution, file compaction, retention, and storage tiering to improve performance and reduce storage costs.
- Design, configure, and maintain foundational compute engines and query layers, including AWS EMR, Athena, and Redshift.
- Define infrastructure and access patterns for enterprise data marts, optimizing underlying engines for heavy, concurrent BI and reporting queries.
- Architect and enforce data governance, network isolation, encryption at rest and in transit, and fine-grained access controls using AWS Lake Formation and IAM.
- Provision, deploy, and version-control data platform infrastructure through automated, reproducible infrastructure-as-code practices.
- Monitor and optimize AWS data spending, and plan capacity to support growth in data volume.
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 arrangement 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
