Senior Data Architect Lead

As Senior Data Architect / Lead youll define how data is structured and ensure it flows seamlessly from source to production ML. This role blends architecture modeling and ML enablement. Youll design the data foundations for model development and deployment working with Data Science and Platform teams to ship models safely but wont own 24/7 infra or MLOps tooling.

What Youll Own

• Data Architecture & Strategy: Define enterprise data architecture for analytics BI and ML use cases. Set the roadmap for real-time batch data
• Model Development Enablement: Architect feature pipelines training data layers and semantic models that accelerate DS teams. Own feature store design and data contracts for ML
• Model Deployment Design: Partner with ML & Platform Engineering to architect deployment patterns for batch and real-time inference. Define standards for model data inputs monitoring data and rollback
• Data Modeling: Lead design of canonical models and warehouses that serve both analysts and production models
• Data Governance for ML: Establish lineage auditability and quality checks for training inference data. Ensure PDPA/GDPR compliance for model features
• Platform Guardrails: Define requirements for serving layers online stores and monitoring but Platform Engineering builds/runs them
• Stakeholder Leadership: Bridge Product Analytics Data Science and Engineering to deliver data ML solutions
• Team Enablement: Mentor engineers on building production-grade data products. Review designs for model-facing datasets

What Youll Need

• Experience: 10 years in data with 3 years as a Data Architect Lead Data Engineer or ML-adjacent architect
• Data Modeling Mastery: Expert in dimensional modeling feature engineering and designing for both BI ML consumption
• Model Lifecycle Exposure: Hands-on experience across model dev and deployment youve shipped features to prod defined inference schemas or designed monitoring datasets. Understand batch vs online serving tradeoffs
• SQL & Warehousing: Deep expertise in BigQuery Snowflake Redshift or Databricks
• Architecture Skills: Designed large-scale platforms supporting training batch inference and real-time scoring
• Tech Fluency: Strong SQL Python. Can read/write dbt. Understand Airflow Spark feature stores and model registry concepts
• Communication: Can align DS Eng and Product on data contracts and deployment standards