Data Platform and Observability Engineering Technical Lead

Job Summary

We are looking for a technical lead to own the technical vision and architecture for Workday's data-product platform, a highly scalable lakehouse that lets teams build, govern, and operate data products and marts.

Responsibilities

• Architect and build the data-product platform on dbt Core, Airflow, Trino, Apache Iceberg, S3 Tables, and Glue Catalog, designed for high-volume ingestion and interactive query performance.
• Own the platform path teams use to ship products: project structure, orchestration, CI/CD, environments, semantic / metrics definitions, and operational support.
• Drive performance and scaling across modeling and query paths: Iceberg layout and maintenance, partitioning, incremental processing, compression, and Trino tuning under production load.
• Lead HA/DR design for platform services , multi-AZ resilience, failover, backup/restore, and recovery objectives appropriate to a shared production platform.
• Design security and access-control architecture, including authentication and authorization for multi-tenant data access across catalog, compute, storage, and visualization.
• Use Terraform to define how the platform is built and evolved; set the bar for infrastructure, environments, and blast radius.
• Own operational excellence: monitoring, alerting, capacity planning, safe reruns and backfills, and participation in an on-call rotation for the platform.
• Evaluate and introduce new technologies, open source and cloud-native, that materially improve scalability, cost efficiency, governance, or developer experience.
• Shape how teams use the platform: reusable dbt and modeling patterns, data-quality frameworks, and a visualization layer (Apache Superset, Metabase, or equivalent) connected to governed catalogs and Trino.
• Evangelize the platform: publish best practices, mentor engineers across DPOE and partner teams, and act as a technical thought leader for the modern lakehouse and data-product stack internally.
• Operate with high autonomy in a fast-moving, ambiguous environment, setting technical direction with minimal oversight while aligning with broader platform strategy.

Requirements

• 14+ years experience in software development engineering.
• 6+ years experience specifically focused on designing, building, and operating complex distributed system architectures, evidenced by successful deployment of systems with high availability (e.g., 99.9% uptime) and fault tolerance.
• 8+ years experience with at least two of the following programming languages (e.g., Java, Python, Go), including experience in writing production-level code for distributed systems.
• Bachelor’s degree in a relevant field such as Computer Science, Engineering, or a related discipline; a Master’s degree (e.g., MS in Computer Science, Distributed Systems, or related field) is strongly preferred or equivalent practical experience.

Nice to Have

• Expert-level ability in algorithmic thinking to architect highly efficient and scalable solutions for high-volume data and interactive query workloads.
• Deep expertise in API development, including advanced API protocols or architectural patterns around query engines, catalogs, and platform services.
• Deep understanding of distributed systems principles, including partitioning, consensus or coordination, fault tolerance, and failure recovery.
• Proven ability to design and implement high-availability strategies for critical distributed data systems.
• Extensive experience with large-scale data processing and lakehouse platforms (for example Kafka, Spark, Flink, Airflow, Trino, Apache Iceberg, Amazon S3 / S3 Tables, AWS Glue Data Catalog).
• Production dbt Core experience at scale: large model graphs, testing and data-quality frameworks, incremental models, and reusable project architecture.
• Strong production SQL and data-modeling experience, including query and physical-layout optimization.
• Experience using Terraform (or equivalent) to design and operate production cloud infrastructure for a data platform.
• Experience designing multi-tenant access control, IAM, encryption, and governed access for analytical data.
• Experience with a visualization or semantic layer such as Apache Superset, Metabase, Looker, or comparable tools.
• Deep understanding of large-scale systems design: distributed data management, scalability, and cost-aware architecture.
• Strong understanding of system security principles for complex distributed data environments.
• Proven ability to lead collaboration within and across software teams and to drive architectural direction.
• Strong technical writing, documentation, and presentation skills.

What We Offer

• Annualized base salary range: $222,900 USD - $334,300 USD
• Workday Bonus Plan or a role-specific commission/bonus
• Annual refresh stock grants
• Comprehensive benefits
• Flexible work arrangements