Senior Data Architect

Oura Oura · Consumer · San Francisco, CA +1 · Data Engineering & Analytics

Senior Data Architect responsible for setting data foundations and models for Data Products, focusing on a unified data mesh platform. The role involves designing structural foundations for interoperable, scalable, and trustworthy data products, with a specific emphasis on AI readiness, including vector-based architectures and RAG patterns for LLM reporting and Agentic AI. Experience with Databricks, Google Big Query, Snowflake, and implementing federated data governance for privacy and compliance (HIPAA/PHI) is required.

What you'd actually do

  1. Design and manage data domains to enable the creation of interoperable, trustworthy data products.
  2. Build and optimize Oura’s Data Lakehouse leveraging Databricks, Google Big Query, and Snowflake to process Terabyte-Petabyte scale data.
  3. Implement federated data governance within the data mesh to ensure processes meet privacy, compliance (HIPAA/PHI), and security requirements.
  4. Partner with Data Engineering, Data Science, and Business Domain owners to advocate for unified analytics and modeling best practices.
  5. Design vector-based data architectures and Retrieval Augmented Generation (RAG) patterns to enable LLM reporting and Agentic AI.

Skills

Required

  • Data architecture or modeling (8+ years)
  • Cloud-based platforms (AWS, GCP, Databricks or Azure)
  • Databricks
  • Google Big Query
  • Snowflake
  • Data Mesh principles
  • Federated data governance
  • HIPAA
  • PHI
  • Vector-based data architectures
  • Retrieval Augmented Generation (RAG)
  • Agentic AI
  • AWS (S3, Kinesis, Glue, Athena)
  • GCP (BigQuery, VertexAI)
  • Azure
  • Docker
  • Pulumi
  • Workflow engines
  • Master Data Management (MDM)
  • Reference Data Management (RDM)
  • Iceberg
  • dbt
  • dbt Cloud
  • AI/ML integration
  • VertexAI
  • MLOps frameworks
  • Large Language Models (LLM)
  • Predictive analytics
  • Anomaly detection
  • Automated reporting
  • Data residency requirements
  • Privacy standards
  • Data accuracy, reliability, and trustworthiness
  • Kafka
  • Kinesis
  • Python
  • Spark
  • SQL
  • Fivetran
  • Airflow
  • Dagster
  • Databricks Lakeflow

Nice to have

  • LLM reporting

What the JD emphasized

  • Data Mesh
  • HIPAA/PHI
  • Agentic AI
  • RAG
  • vector-based data architectures

Other signals

  • AI Readiness
  • LLM Reporting
  • Agentic AI
  • RAG
  • Vector-based data architectures