Data Architect

Description

• Build & evolve the semantic layer - design subject area models, define conformed dimensions and governed metrics, and expose them for BI, APIs, and AI agents
• Lead scaling of the Master data (Project, Vendor, Budget, People etc.) and golden record rules
• Define and monitor SLAs with incident playbooks
• Partner with Data Science to integrate governance checkpoints into pipelines
• Implement and maintain lineage, technical and business metadata, and documentation across Databricks Unity Catalog; ensure LLM-friendly metadata for RAG and AI agents
• Ensure adherence to all applicable data regulations and policies
• Partner with CISO to maintain security of cloud infrastructure for analytics and AI
• Extract business rules currently embedded in dashboards / SQL and refactor them into reusable transformations, tests, and metric definitions
• Deploy and maintain data catalog across Databricks
• Embed rule-based and ML anomaly tests into pipelines and semantic layer
• Own annual assessments and audits for analytical data stack
• Drive continuous improvement to cut quality issues by 90 % year-over-year
• Champion “data-as-a-service” culture—making trusted data and insights the default for project teams
• Own the target architecture for Databricks on AWS (S3/EC2, Delta Lake, Unity Catalog, MLflow/Model Registry, Delta Live Tables) and the interfaces to Agentic AI stack/BI/IDE and downstream apps
• Establish model registry, bias/drift monitoring, and audit trails for all predictive and GenAI models
• Develop and implement data classification and access framework
• Plan platform evolution (governed multi-workspace layout, environment separation, lineage/observability) and drive high-impact upgrades and migrations with low downtime
• Champion IaC & CI/CD (e.g., Terraform + GitHub Actions) for reproducible workspaces, catalogs, pipelines, and policies
• Design ingestion and serving patterns, data contracts, and API/SQL access layers for internal consumers and agentic use cases

Requirements

• Proven track record standing up enterprise catalog/lineage and data quality automation
• 5+ years in data architecture/engineering within a modern cloud stack; 2+ years owning a semantic/metrics layer at scale
• Excellent stakeholder skills, able to translate governance concepts to the broader teams
• Strong SQL/Python with Delta Lake, Unity Catalog, MLflow/Model Registry; experience with Delta Live Tables (or equivalent) for transformations
• Working knowledge of access control patterns, data classification, and PII protections in analytical stacks; partners effectively with security teams

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance