Chief Architect - Data Engineering (Databricks Practice)

We are building a fast-growing Databricks practice delivering enterprise data and AI solutions across APAC. As Lead Solution Architect – Data Engineering, you will be the technical anchor of the practice: leading solution design on client engagements, owning and defending enterprise architectures in presales, and driving large-scale migration and cloud transformation programs. This is a hands-on leadership role for a builder who can equally command a whiteboard in front of a CTO and a Spark UI when a pipeline misbehaves. You will also shape the practice itself — mentoring engineers, creating accelerators and reusable assets, and converting delivery success into case studies and go-to-market offerings. Architecture & Delivery Own end-to-end architecture and design decisions on Databricks engagements, ensuring solutions are secure, scalable, performant, and aligned with Lakehouse best practices. Lead delivery of production-grade data platforms — ingestion, transformation, orchestration, governance through Unity Catalog, and downstream BI/ML enablement. Lead large-scale migrations (legacy DW/ETL, Hadoop, on-prem estates) and cloud transformation projects to Databricks on Azure/AWS/GCP, including assessment, wave planning, and cutover. Stay hands-on: performance tuning, debugging, code and design reviews, and setting engineering standards for the team. Presales & Stakeholder Management Own and defend enterprise solution designs in front of architecture boards, CIOs, and CTOs — and enjoy it. Drive presales end-to-end: discovery, solutioning, estimation, PoCs, RFPs, and proposals that convert. Translate hard technical trade-offs into decisions executives can act on — from engineer to boardroom without changing gears. Who Thrives Here A builder at heart — 12+ years in data engineering/architecture, 3+ on Databricks at enterprise scale, and still happiest when hands are on the keyboard. Deep Spark expertise — architecture, performance tuning, streaming, debugging, the advanced stuff that separates architects from diagram-drawers. Lakehouse fluency — Medallion architecture, Delta Lake, Unity Catalog, governance, orchestration (Workflows, DLT/Lakeflow, Airflow, ADF); Microsoft Fabric exposure a bonus. Battle-tested in migrations — you've led large transformation programs and have the scars and success stories to show for it. Presales instinct — you don't just design solutions; you sell them, price them, and defend them under fire. Modern edge — strong Python/SQL/Scala, CI/CD for data platforms, and comfort integrating ML/AI (MLflow, LLM APIs like OpenAI and Anthropic) into what you build. Certified credibility — Databricks Data Engineer Professional / SA accreditations strongly preferred. Founder energy — curiosity, adaptability, and the drive to build offerings, not just deliver projects

You will lead end-to-end architecture and delivery for Databricks engagements, ensuring scalable and performant data platforms. Additionally, you will drive presales activities, including solution design, estimation, and stakeholder management at the executive level.

Candidates must have over 12 years of experience in data engineering and architecture, with at least 3 years specifically in Databricks at an enterprise scale. Strong expertise in Spark, cloud migrations, and modern data stack technologies is required, along with a proven ability to lead technical teams and client engagements.

• Microsoft AzurePreferred
• SQLPreferred
• Machine learningPreferred
• Amazon Web ServicesPreferred
• Google CloudPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Databricks
• Data Engineering
• Solution Architecture
• Spark
• Python
• SQL
• Scala
• Delta Lake
• Unity Catalog
• Cloud Transformation
• Presales
• Azure
• AWS
• GCP
• Machine Learning
• Data Governance
• Case Study
• Go-to-Market Strategy
• Solution Design
• Distributed Ledgers
• CI/CD
• MLflow
• Workflow Management
• Curiosity
• Apache Airflow
• Microsoft Fabric
• Planning
• Adaptability
• Application Programming Interface (API)
• Artificial Intelligence
• Amazon Web Services
• Microsoft Azure
• Business Intelligence
• Convergent Technologies Operating Systems
• Extract Transform Load (ETL)
• Data Warehousing
• Debugging
• Governance
• Leadership
• Apache Hadoop
• Scalability
• Python (Programming Language)
• Mentorship
• Performance Tuning
• Request For Proposal
• Scala (Programming Language)
• SQL (Programming Language)
• Stakeholder Management
• On Prem

• Data & Analytics
• Technology
• Software
• Consulting
• Management & Leadership
• Data Engineer/Architect
• Data Engineer
• Software Developers
• Database Administrators

Minimum education

Professional degree

Minimum experience

10+ years

Posting language

English

Working hours

40 hours per week