AI Data Architect

Posted 13hrs ago

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AI Data Architect to design and govern the AI data platform at 3Pillar, facilitating AI initiatives across various business sectors.

Architect and own the enterprise AI data platform — the unified, governed layer that ingests, transforms, stores, and serves all data consumed by AI systems across the organisation.
Design multi-domain data models (lakehouse, data mesh, event-driven) that are structured from day one to serve AI workloads: clean lineage, versioned schemas, well-documented contracts, and low-latency serving APIs.
Define tools & technologies to develop automated data pipelines, write ETL processes, develop dashboard & report and create insights

15+ years of hands-on data engineering and architecture experience, alongside building production AI/ML and LLM-era data infrastructure.
Strong Experience with either Databricks or Snowflake; experience with both is desirable.
Strong data architecture patterns & principles, ability to design secure & scalable data lakes, data warehouse, data hubs, and other event-driven architectures
Expertise in designing and writing ETL processes in Python / Java / Scala
Own the full data stack: real-time streaming (Kafka, Spark Structured Streaming), batch processing (Databricks, PySpark, Delta Lake), cloud storage and compute (AWS, Azure), and data quality /metadata management.
Drive modernisation of legacy pipelines (on-prem ETL, batch DWH) to cloud-native, AI-ready architectures with measurable improvements in cost, latency, and delivery velocity.
Proven experience designing enterprise-scale AI data platforms that serve multiple AI consumers —not just one application or pipeline.
Hands-on experience with vector stores, semantic models, knowledge graphs, and retrieval infrastructure in production environments.
Working knowledge of LLMOps: model serving pipelines, MLflow, CI/CD for AI, automated evaluation, and production monitoring.