Sr. Data Engineer - Cybersecurity

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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 & Platform 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 Logistics (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 Senior Data Engineer to serve as the Subject Matter Expert (SME) for Data Logistics. In this role, you will be the driving force behind how data moves, transforms, integrates, and is discovered across our ecosystem. While the platform team builds the underlying infrastructure, your mission is to design the high‑performance pipelines, complex ETL/ELT workflows, and data enrichment layers that turn raw streams into trusted, business‑ready data assets.

Crucially, you will own the usability and integrity of our data assets. You will lead the charge on data documentation, cataloguing, Master Data Management (MDM), and the design of downstream data marts, ensuring that our data is not just flowing, but is clean, standardised, governed, and highly discoverable for the entire enterprise.

• Pipeline & ETL/ELT Architecture: Design, implement, and optimize highly scalable, resilient data ingestion and transformation pipelines from disparate internal and external sources.
• Data Enrichment & MDM: Lead the strategy for Master Data Management (MDM) within our pipelines. Architect sophisticated data stitching, deduplication, and enrichment processes to establish a single source of truth for core business entities.
• Data Reliability & Observability: Implement comprehensive data quality and observability frameworks (e.g., data profiling, anomaly detection, SLA tracking) to ensure absolute trust in pipeline outputs.
• Data Mart & Semantic Layer Design: Architect and build optimized, user‑focused Data Marts and semantic layers. Translate complex source data into clean, dimensional models (Kimball/Inmon, Star Schema) tailored for business intelligence and analytics.
• Data Cataloging & Documentation: Serve as the primary champion for data discoverability. Build, maintain, and automate enterprise Data Dictionaries, Data Catalogs, and Data Logs to ensure data lineage and definitions are transparent across the org.
• Data Governance Enforcement: Partner with compliance and platform teams to embed data governance policies directly into the logistics lifecycle (e.g., automated PII masking, data retention, access tiering at the pipeline level).
• Technical Mentorship: Act as the technical anchor for the data engineering squad, setting engineering standards for code quality, workflow documentation, and pipeline design.

About You

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

Required Technical Skills & Experience**

• Experience: 5+ years of hands‑on data engineering experience, with a heavy focus on complex pipeline development, data modeling, and governance metadata patterns.
• AWS Data Ecosystem: Advanced, hands‑on experience with AWS Glue (ETL, catalogs, schema registry, workflows) and AWS EMR (Spark engine tuning).
• Distributed Computing: Deep proficiency with Apache Spark (PySpark or Scala) for large‑scale data processing and transformation.
• Data Modeling & Architecture: Expert knowledge of data warehousing concepts, including Star/Snowflake schemas, dimensional modeling, and building curated Data Marts.
• Languages: Expert‑level Python and SQL (including advanced analytical functions and performance tuning).

• Governance & Cataloging Tools: Hands‑on experience working with modern data catalog and governance tools (e.g., OpenLineage, dbt docs, Collibra, Alation, Apache Atlas, or AWS Glue Data Catalog).
• Orchestration: Strong experience with Apache Airflow, Prefect, or AWS Step Functions to manage complex, multi‑stage DAGs.
• Data Lakehouse & Warehouse Architecture: Experience designing and optimizing scalable data lake‑house or warehousing patterns (e.g., Medallion Architecture, Data Mesh, or open‑table format strategies like Apache Iceberg/Delta Lake) to support high‑performance analytics.
• CI/CD & Engineering Best Practices: Experience implementing robust CI/CD pipelines (e.g., GitHub Actions, Jenkins) for data assets, including automated unit/integration testing,infrastructure‑as‑code(IaC) using Terraform or CDK, and GitOps workflows to ensure reproducible and high‑quality deployments.

Workday Pay Transparency Statement (For EU Locations Only)

Listed below is the base salary range applicable to this position. Workday pay ranges (and the precise pay offered to the successful candidate) are based on a number of objective criteria such as relevant experience and skills, and educational qualifications, level of responsibility, demands of the role, work location and business need. 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 awarded by Workday Inc. For more information regarding Workday’s comprehensive benefits, please click here.

Primary Location Base Pay Range: €86,400 EUR - €129,600 EUR Ireland