Senior Cybersecurity Data Engineer - Data Platform & Lakehouse Sme

Workday Workday · Enterprise · USA.VA.Reston

Workday is seeking a Senior Data Engineer to be the Subject Matter Expert (SME) for Data Platform and Lakehouse Architecture. This role will focus on building, securing, and optimizing the data lake, storage layers, and compute infrastructure for their cybersecurity data platform. Responsibilities include designing the Data Lakehouse on AWS, optimizing storage formats, scaling compute infrastructure, architecting data marts, implementing security and access controls, and using Infrastructure as Code. The role requires deep experience in data platform engineering, AWS data services, and open-table formats.

What you'd actually do

  1. Lead the design, infrastructure implementation, and evolution of our enterprise Data Lake/Lakehouse ecosystem on AWS.
  2. Serve as the ultimate authority on modern open-table formats (Apache Iceberg or Delta Lake). Define the standards for partition strategies, schema evolution, file compaction, retention, and storage tiering to maximize performance and slash storage costs.
  3. Design, configure, and maintain the foundational compute engines and query layers (e.g., AWS EMR clusters, AWS Athena, Redshift) utilized by downstream data engineers, analysts, and BI tools.
  4. Define the foundational infrastructure and access patterns for enterprise Data Marts. Ensure underlying engines are optimized to handle heavy, concurrent query loads from downstream BI and reporting tools.
  5. Architect and enforce global data governance, network isolation, encryption (at rest and in transit), and fine-grained access controls using AWS Lake Formation and AWS IAM.

Skills

Required

  • 5+ years of deep experience in data platform engineering, cloud infrastructure engineering, or data architecture
  • proven track record of designing large-scale enterprise data lakes
  • Expert-level knowledge of open-table formats (Apache Iceberg or Delta Lake)
  • deep understanding of file format internals (Parquet, ORC, metadata layers)
  • Advanced, production-level expertise across the AWS data stack, specifically AWS EMR (Spark/Presto/Trino tuning), AWS Athena, S3 infrastructure, and AWS Lake Formation.
  • Advanced proficiency with Terraform or AWS CDK for provisioning secure, multi-environment data infrastructures.
  • Deep understanding of modern cloud data warehouses (Snowflake, Databricks, or AWS Redshift) and cluster sizing/workload management.
  • Advanced proficiency in SQL (performance tuning, query optimization)
  • Python or Bash for infrastructure automation

Nice to have

  • AWS Certified Solutions Architect – Professional or AWS Certified Data Engineer
  • Experience setting up multi-region data lakes, cross-account data sharing, or data mesh architectures.
  • Experience with open-source query engines like Trino or StarRocks.

What the JD emphasized

  • Subject Matter Expert (SME) for Data Platform and Lakehouse Architecture
  • foundational architect of our data universe
  • build, secure, and optimize the actual bedrock
  • define how data is physically stored, partitioned, and accessed
  • establish the frameworks, compliance guardrails, and compute engine standards
  • ultimate authority on modern open-table formats
  • Expert-level knowledge of open-table formats (Apache Iceberg is highly preferred, or Delta Lake)
  • Advanced, production-level expertise across the AWS data stack, specifically AWS EMR (Spark/Presto/Trino tuning), AWS Athena, S3 infrastructure, and AWS Lake Formation.
  • Advanced proficiency with Terraform or AWS CDK for provisioning secure, multi-environment data infrastructures.