Chief Architect – Data Engineering (Databricks)

About the role

We are expanding a fast‑growing Databricks practice across APAC and need a senior technical leader to own solution design, presales, and large‑scale migrations. As Chief Architect – Data Engineering you will be the technical anchor, guiding both client engagements and internal delivery teams.

Key responsibilities

• Define end‑to‑end architecture for Databricks engagements, ensuring security, scalability, performance and Lakehouse best practices.
• Lead delivery of production‑grade data platforms covering ingestion, transformation, orchestration, governance (Unity Catalog) and downstream BI/ML enablement.
• Drive large‑scale migrations from legacy DW/ETL, Hadoop or on‑prem environments to Databricks on Azure, AWS or GCP, including assessment, wave planning and cut‑over.
• Stay hands‑on with performance tuning, debugging, code and design reviews, and set engineering standards for the team.
• Own and defend enterprise solution designs in front of architecture boards, CIOs and CTOs.
• Manage presales activities: discovery, solutioning, estimation, PoCs, RFPs and proposal creation.

Required profile

• 12+ years of experience in data engineering/architecture, with at least 3 years on Databricks at enterprise scale.
• Deep expertise in Apache Spark, including architecture, performance tuning, streaming and debugging.
• Strong knowledge of Lakehouse concepts such as Medallion architecture, Delta Lake, Unity Catalog and data governance.
• Proven ability to lead complex migration and cloud transformation projects.
• Excellent communication skills to translate technical trade‑offs to executive audiences.

Required skills

• Python
• Scala
• SQL
• Apache Spark
• Databricks
• Delta Lake
• Unity Catalog
• Airflow
• ADF (Azure Data Factory)
• DLT / Lakeflow
• MLflow
• OpenAI / Anthropic APIs
• Microsoft Fabric
• Lakehouse / Medallion architecture