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Chief Architect - Data Engineering (Databricks Practice)

Offre en anglais

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.

  • Sur place
  • Toronto, ON
  • Publié 20 août 2026
  • Postuler avant le 16 févr. 2027
  • 1 poste

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Résumé du poste

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

Ce que vous ferez

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.

Exigences

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.

Compétences indiquées

  • Microsoft AzureSouhaitée
  • SQLSouhaitée
  • CI/CDSouhaitée
  • Amazon Web ServicesSouhaitée
  • Google CloudSouhaitée
  • PythonSouhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • Databricks
  • Apache Spark
  • Data Engineering
  • Lakehouse Architecture
  • Unity Catalog
  • Python
  • SQL
  • Scala
  • Cloud Transformation
  • Presales
  • Delta Lake
  • CI/CD
  • MLflow
  • Azure
  • AWS
  • GCP

Domaines d’emploi

  • Data & Analytics
  • Technology
  • Consulting
  • Software
  • Management & Leadership

Renseignements supplémentaires

Formation minimale
Diplôme professionnel
Expérience minimale
10+ ans
Postuler avant le
16 févr. 2027
Langue de l’offre
anglais
Heures de travail
40 heures par semaine
Niveau d’expérience
Mid-Senior level
Mode de candidature
La candidature directe est offerte