Chief Architect - Data Engineering (Databricks Practice)
- Toronto, ON, Canada
Full-time
Applications open in a new tab.
Job details
- Job type
- Full-time
- Apply by
- Posting language
- English
- Posted
Original job description
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
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
- 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
- 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
More about this job
Responsibilities
Lead the end-to-end architecture and delivery of enterprise data and AI solutions using Databricks across the APAC region. Drive presales activities, including solution design and proposals, while mentoring engineers and creating reusable practice assets.
Requirements
Requires over 12 years of experience in data engineering with at least 3 years of enterprise-scale Databricks expertise. Candidates must be proficient in Spark, Lakehouse patterns, and cloud migrations, with strong presales instincts and professional certifications preferred.
Skills
- Databricks
- Apache Spark
- Data Engineering
- Lakehouse Architecture
- Unity Catalog
- Python
- SQL
- Scala
- Cloud Transformation
- Presales
- Delta Lake
- CI/CD
- MLflow
- Azure
- AWS
- GCP
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Consulting
- Software
- Management & Leadership
Keywords
- Databricks
- Apache Spark
- Lakehouse
- Medallion Architecture
- Delta Lake
- Unity Catalog
- Workflows
- DLT
- Lakeflow
- Airflow
- ADF
- Microsoft Fabric
- Python
- SQL
- Scala
- CI/CD
- MLflow
- LLM APIs
- OpenAI
- Anthropic
- Azure
- AWS
- GCP
- Data Engineering
- Cloud Transformation
- Presales
- Enterprise Architecture
- Data Platforms
- ETL
- Hadoop