Lead the design of decentralized Data Mesh architectures, manage scalable data ecosystems, implement data governance, and mentor engineers in a hybrid working model.
Principal Data Architect – Modern Data Platforms & Data Mesh San Jose, CA | Newport Beach, CA | Hybrid (2–3 days onsite)
Role Overview
We are seeking a highly experienced, hands-on Principal Data Architect to define the strategic vision for a next-generation, petabyte-scale data platform and lead the transition from centralized to decentralized data management. This is a principal-level role — the bar goes well beyond senior. We are looking for someone with demonstrated long tenure at complex, large-scale data environments who has driven real architectural transformation, not just advised on it.
The core mandate is data decentralization — moving from a monolithic data warehouse model to a Data Mesh paradigm — alongside modernizing data security, governance, and real-time capabilities. Consulting backgrounds and serial short-tenure candidates will face significant additional scrutiny; we want people who have gone deep and have the organizational impact to show for it.
What You'll Do
Strategic Architecture & Data Mesh
- Lead the design and implementation of a scalable, decentralized Data Mesh architecture; define domain boundaries, data products, and federated governance standards
- Drive the organization from centralized to decentralized data management — change management experience is as important as technical depth
- Establish data contracts and self-service analytics capabilities across the organization
Hands-On Engineering Leadership
- Architect and prototype resilient data pipelines using Databricks, Snowflake, and Spark, ensuring high availability and low latency
- Drive adoption of open table formats (Delta Lake, Apache Iceberg) for ACID compliance, time travel, and schema evolution across the data lakehouse
- Troubleshoot complex performance bottlenecks in distributed systems
Data Security & Governance
- Architect advanced data security patterns including dynamic data masking, tokenization, and row-level security
- Implement centralized discovery and access control using Unity Catalog or equivalent enterprise data catalogs
- Implement technical controls for data privacy regulations (GDPR, CCPA) including encryption at rest and in transit
Real-Time & Event-Driven Systems
- Design and deploy high-throughput streaming architectures using Kafka or Pulsar for real-time data ingestion and processing
- Deep understanding of workflow orchestration tools (Airflow, dbt, Dagster)
MLOps & Analytics Integration
- Build robust MLOps pipelines and feature stores bridging data engineering and production AI/ML
- Collaborate with data scientists to operationalize machine learning models end-to-end
Technical Leadership & Culture
- Mentor senior data engineers and architects; foster a culture of technical excellence and "Data as a Product" thinking
- Treat data pipelines as code — strict CI/CD, unit testing, and version control practices expected
About You
Experience & Background
- 10+ years of software and data engineering experience, with a significant portion in technical leadership or architecture
- FAANG or Big Tech background strongly preferred
- Proven track record at large-scale enterprise environments — petabyte-scale data infrastructure is the baseline expectation
- Long tenure at key roles is a strong positive signal; we are not looking for contract-to-contract backgrounds or candidates with a pattern of 1–2 year stints
- Consulting backgrounds are not disqualifying but will be scrutinized — be prepared to speak specifically to what you owned vs. what you touched
Technical Requirements
- Data Mesh: proven experience transforming monolithic data warehouses into decentralized Data Mesh architectures including federated governance
- Platforms: deep hands-on expertise with Databricks and Snowflake including compute optimization and cost management
- Big Data: strong proficiency in Apache Spark, Delta Lake, Iceberg, and Hudi
- Coding: expert-level Python, SQL, and Scala/Java nice to have
- Streaming: Kafka or Kinesis; orchestration via Airflow, dbt, or Dagster
- Governance: hands-on with Unity Catalog, Alation, or Collibra
- MLOps: solid understanding of model registry, feature stores, and model serving
Location & Work Model
Hybrid position based out of San Jose, CA or Newport Beach, CA — candidates must be within commutable distance of one of these two offices. Onsite 2–3 days per week expected. Out-of-area candidates considered only in exceptional circumstances and held to a significantly higher bar.
Compensation
Competitive base compensation commensurate with experience. 25% target bonus. Full benefits including medical/dental/vision, retirement plans, paid parental leave, and paid time off.
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