Senior Cybersecurity Data Engineer - Data Platform & Lakehouse SME

Your work days are brighter here. 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. About the Team We are a newly formed, forward-looking Cybersecurity Data Engineering & Enablement Team driving the future of our enterprise defense strategy. Our mission is to build a next-generation, centralized data lakehouse that unifies all security telemetry into a single, high-performance ecosystem. Operating across two specialized verticals—Data Engineering (ingestion, enrichment, and semantic layers) and Data Platform (foundational infrastructure, security architecture, and AI enablement)—we are designing a scalable, cloud-native foundation from the ground up. By combining cutting-edge data architecture with advanced analytics, we empower our threat hunters, data scientists, and incident responders with the real-time, trusted intelligence needed to protect the enterprise at scale. About the Role 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. About You Basic Qualifications Experience: 5+ years of deep experience in data platform engineering, cloud infrastructure engineering, or data architecture, with a proven track record of designing large-scale enterprise data lakes. Table Formats & Storage: Expert-level knowledge of open-table formats (Apache Iceberg is highly preferred, or Delta Lake) and deep understanding of file format internals (Parquet, ORC, metadata layers). AWS Cloud Native Data Infrastructure: Advanced, production-level expertise across the AWS data stack, specifically AWS EMR (Spark/Presto/Trino tuning), AWS Athena, S3 infrastructure, and AWS Lake Formation. Infrastructure as Code (IaC): Advanced proficiency with Terraform or AWS CDK for provisioning secure, multi-environment data infrastructures. Data Warehousing Foundations: Deep understanding of modern cloud data warehouses (Snowflake, Databricks, or AWS Redshift) and cluster sizing/workload management. 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. Workday Pay Transparency Statement 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. Primary Location: USA.VA.Reston Primary Location Base Pay Range: $159,600 USD - $239,400 USD Additional US Location(s) Base Pay Range: $144,400 USD - $258,000 USD Our Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records. Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans. At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email View email address on click.appcast.io. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. 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