Databricks Data & AI Analytics Architect

About the role

We are looking for an experienced Data & AI Analytics Architect / Lead Engineer to modernize enterprise analytics platforms and accelerate AI‑powered insights on Databricks. The role will design and implement scalable data ingestion frameworks, metadata‑driven architectures, and conversational analytics that enable faster, governed decision‑making across trading, risk, finance and operations.

Key responsibilities

• Modernize legacy analytics platforms by migrating workloads to Databricks.
• Design and build scalable data ingestion and ELT pipelines using Spark, Delta Lake and watermark processing.
• Create metadata‑driven architectures and implement Unity Catalog for data governance and lineage.
• Develop conversational analytics and AI/LLM‑powered assistants to enable self‑service insights.
• Ensure high performance, reliability and auditability of analytical workloads.

Required profile

• Proven experience designing enterprise‑scale data ingestion, ETL/ELT and metadata‑driven frameworks.
• Strong background in SQL optimization, semantic modeling and building governed data products.
• Ability to collaborate with business and technology teams to improve data availability and reliability.
• Familiarity with trading, risk, finance or operations domains is highly desirable.

Required skills

• Databricks (including Unity Catalog, SQL Warehouses, Workflows, Genie, Genie One)
• Apache Spark and Delta Lake
• ETL/ELT pipeline development with watermark processing
• Advanced SQL query optimization and semantic modeling
• AI/LLM‑powered analytics and conversational interfaces
• Analytical assistants / copilots leveraging business metadata and governance rules
• KPI monitoring, trend analysis, anomaly detection and automated executive summaries
• Cloud data and analytics architecture design (ingestion, transformation, modeling, serving)