Staff/Principal AI Data Lead

About the Role We are seeking a Staff/Principal AI Data Lead to modernize our enterprise data ecosystem so it is ready to support building new AI and ML tools. This role focuses on data readiness, governance, quality, and secure access, defining standards, contracts, and observability to make data trustworthy, discoverable, and easy to consume. We currently focus on an Airflow-centric approach and the role will help guide decisions about data infrastructure and tooling. What You'll Do

• Define the enterprise AI data architecture vision, principles, and reference architectures.
• Lead cross-functional reviews with IT, security, legal/privacy, and business stakeholders to align on data readiness roadmaps.
• Establish data contracts for AI consumption (schemas, semantics, classifications, SLAs) and govern schema evolution; make the data catalog the system of record for lineage, ownership, definitions, and policy labels.
• Define standard data models and semantic conventions that improve joinability and reuse across domains.
• Implement an enterprise data quality framework and automated scorecards (freshness, completeness, accuracy, consistency). Monitor for anomalies and schema drift; publish AI data readiness dashboards (catalog coverage, lineage depth, PII detection coverage, contract adherence).
• Standardize patterns for ingestion, processing, storage, serving, and environment promotion using Airflow or other standard ETL/Orchestration tools and CI/CD for data workflows.
• Define secure, consistent access patterns/APIs for downstream analytics and AI consumers.
• Drive the foundational architecture and standards necessary to enable advanced Retrieval Augmented Generation (RAG) and semantic search capabilities across the enterprise. Provide guidance for chunking/segmentation policies, deduplication, and hybrid search compatibility; downstream teams implement embeddings/vector stores.
• Define safe-access patterns for AI consumption to prevent sensitive data exposure. Enforce security baselines (encryption, RBAC/ABAC, masking/tokenization) and policy-as-code for access.
• Architect for transparent cost attribution and controls (tagging, storage tiering, retention) to enable informed cost/performance choices by consumers. Assist leadership by making recommendations to improve efficiency and create automated triggers to identify planned budget allocation violations.
• Collaboration and Mentorship: Provide reference templates for AI-ready datasets, contracts, and catalog usage; mentor engineers and analysts on best practices. Collaborate with other system architects to ensure continued reliability and opportunities for overall ecosystem improvement. What We're Looking For
• 8+ years in data engineering/architecture/platform roles, preferably >1 year at Staff/Principal level.
• Expert SQL and Python; track record building enterprise data governance, contracts, and quality frameworks.
• Experience operating production data platforms in batch/near-real-time with strong lineage and access control.
• Practical unstructured data governance (metadata standards, classification, PII detection/redaction).
• Hands-on with catalogs/lineage as systems of record for definitions, ownership, and policy.
• Familiarity with vector/RAG readiness concepts (schemas, metadata, provenance) without owning embeddings/model development.
• Experience with workflow orchestration (e.g. Airflow) and CI/CD/testing for data pipelines. Compensation & Benefits
• Competitive salary package
• Private medical & dental coverage
• Employee Pension Plan
• Life insurance
• Employee Stock Purchase Plan
• Flexible working hours
• Strong collaborative culture
• Volleyball field and grill place next to the office
• Access to wellness facilities and integration events as well as training and broad development opportunities