Senior Data Engineer, Cybersecurity

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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, cataloging, Master Data Management (MDM), and the design of downstream data marts, ensuring that our data is not just flowing, but is clean, standardized, governed, and highly discoverable for the entire enterprise.

Key Responsibilities

• 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 Basic Qualifications 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).
• Other Qualifications: 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: €84,000 EUR - €126,000 EUR Ireland

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.

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