Senior Cybersecurity Data Engineer - Data Platform & Lakehouse SME

We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

We are seeking a powerhouse Senior Data Engineer to serve as the Subject Matter Expert (SME) for Data Platform and Lakehouse Architecture. In this role, you will be the foundational architect of our data universe. While other teams focus on moving data through pipelines or building machine learning models, your mission is to build, secure, and optimize the actual bedrock—the data lake, storage layers, and compute infrastructure—that powers our entire security operations and beyond.

As the Platform SME, you will define how data is physically stored, partitioned, and accessed. You will establish the frameworks, compliance guardrails, and compute engine standards that allow the Data Logistics and AI/ML teams to build their workloads safely, rapidly, and at massive scale.

Key Responsibilities

• Data Lakehouse Architecture: Lead the design, infrastructure implementation, and evolution of our enterprise Data Lake/Lakehouse ecosystem on AWS.

• Storage & Table Format Optimization: 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.

• Compute Infrastructure Scaling: 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.

• Data Mart & Semantic Platform Architecture: 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.

• Security, Identity & Access Management (IAM): 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.

• Infrastructure as Code (IaC): Treat all platform infrastructure as software. Provision, deploy, and version-control the entire data platform environment using automated, reproducible code.

• Cost Governance & Capacity Planning: Proactively monitor, alert, and optimize AWS data spend. Perform capacity planning to ensure the platform scales seamlessly with data volume growth.

Basic Qualifications

• Experience: 7+ years in data platform engineering, cloud infrastructure engineering, or data architecture, supporting large-scale enterprise data lakes.

• Table Formats & Storage: 3+ years operating Apache Iceberg (highly preferred) or Delta Lake in production; expert understanding of file format internals (Parquet, ORC, metadata layers).

• AWS Cloud Native Data Infrastructure: 3+ years production-level experience across the AWS data stack, specifically AWS EMR (Spark/Presto/Trino tuning), AWS Athena, S3 infrastructure, and AWS Lake Formation.

• Infrastructure as Code (IaC): 3+ years using Terraform or AWS CDK for provisioning secure, multi-environment data infrastructures.

• Data Warehousing Foundations: 3+ years of modern cloud data warehouses (Snowflake, Databricks, or AWS Redshift) and cluster sizing/workload management experience.

Other Qualifications

• Languages: Advanced proficiency in SQL (performance tuning, query optimization) and Python or Bash for infrastructure automation.

• 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.

The annualized base salary ranges for the primary location and any additional locations are listed below.  Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.

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