Senior Data Engineer, Workday
Cybersecurity
€84-126k
More information about location
Enterprise AI platform for managing HR and finance
Be an early applicant
Enterprise AI platform for managing HR and finance
1001+ employees
Be an early applicant
€84-126k
More information about location
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 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
What the job involves
- As part of our Security Data Engineering team, you won’t just be engineering pipelines; you’ll be architecting the data-driven foundation that empowers our security organization
- We bridge the gap between raw, disparate security telemetry and the actionable insights required to identify threats, manage vulnerabilities, and reduce risk
- If you are a seasoned Data Engineer who finds satisfaction in solving complex cybersecurity challenges by building systems that make the enterprise measurably safer—this is your mission
- We operate at the intersection of high-scale distributed systems and advanced security analytics, turning massive, noisy security signals into the trusted, business-ready data assets that safeguard our infrastructure and customers
- 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
- 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
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities.. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, WOrkday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & Executive Chair)Annel began his career at Morgan Stanley as a Corporate Finance Analyst. He then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005, where he has served as the CEO ever since.
Carl Eschenbach
(CEO)Carl joined Workday in 2022 as Co-CEO, becoming CEO in 2024. He has also been a Partner at Sequoia Capital since 2016. Previously, he spent 14 years at VMware as President and COO and 3 years at Inktomi Corporation as the VP of North America Sales.
Peter Bailis
(CTO)Prior to joining Workday in 2025, People was a VP of Engineering at Google. He also previously founded Sisu Data, where he served as the CEO for over 5 years.
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