# Data Platform and Observability Engineering Technical Lead **Company**: Workday **Location**: Pleasanton, CA **Work arrangement**: hybrid **Experience**: senior **Job type**: full-time **Salary**: $222,900 USD - $334,300 USD **Category**: Engineering **Industry**: Technology **Apply**: https://workday.wd5.myworkdayjobs.com/en-US/Workday/job/USA-CA-Pleasanton/Principal-Distributed-Systems-Engineer_JR-0110621?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_03c902a9-2e7 ## Description ## 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 ## Skills ### Required - dbt Core - Airflow - Trino - Apache Iceberg - Amazon S3 Tables - AWS Glue Catalog - Terraform - SQL - data modeling - distributed systems - cloud infrastructure ### Nice to have - algorithmic thinking - API development - distributed systems principles - high-availability strategies - large-scale data processing - lakehouse platforms - data visualization - semantic layers --- Source: [Apply at workday.wd5.myworkdayjobs.com](https://workday.wd5.myworkdayjobs.com/en-US/Workday/job/USA-CA-Pleasanton/Principal-Distributed-Systems-Engineer_JR-0110621?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)