Data Lake Architect (Databricks)

Role snapshot

• Title: Data Lake Architect – Databricks
• Location: Toronto, ON (hybrid, 2–3 days on-site)
• Engagement: Full-time, placed with an Augmented enterprise client
• Level: Senior / Lead (8+ years in data, 3+ years as an architect)
• Reports to: Head of Data Platform / Enterprise Architecture

About the role

Augmented is hiring a Data Lake Architect to define and lead the Databricks lakehouse architecture for one of our large enterprise clients in a regulated industry. You will set the target-state design, standards and roadmap, and guide engineering teams as they build and migrate onto the platform.

You will be the senior technical voice with client stakeholders, from data engineers to CIO-level leaders. The work covers platform design, governance, security and cost, and enabling analytics and AI use cases at scale.

Key responsibilities

• Define the target-state data lake / lakehouse architecture on Databricks, including medallion layers, storage layout and workspace topology
• Design the governance model with Unity Catalog: catalogs, schemas, access controls, lineage, data classification and PII handling
• Set engineering standards for ingestion, transformation, streaming, data quality and observability
• Lead migration strategy from legacy warehouses, Hadoop or on-prem data lakes to Databricks, including sequencing and cutover plans
• Architect secure cloud foundations: networking, private connectivity, identity, encryption and environment isolation
• Own platform cost and performance strategy: cluster policies, serverless use, workload sizing and FinOps reporting
• Design data products and serving patterns for BI, data science, ML and GenAI workloads
• Review designs and code, mentor engineers, and run architecture decision records
• Present architecture options, trade-offs and roadmaps to client technical and executive stakeholders
• Contribute to pre-sales solutioning, estimates and proposals with Augmented leadership

Required qualifications

• 8+ years in data engineering or data platforms, including 3+ years in an architect role
• Deep hands-on Databricks experience: Delta Lake, Unity Catalog, Workflows, Databricks SQL and cluster/serverless configuration
• Proven delivery of at least one enterprise-scale data lake or lakehouse from design to production
• Strong cloud architecture skills on Azure or AWS (storage, networking, IAM, security, private endpoints)
• Expert in Spark, Python and SQL, with the ability to review and guide engineering work
• Data modelling across medallion, dimensional and Data Vault patterns
• Track record of migrating legacy data platforms to the cloud
• Experience defining data governance, security and compliance controls in regulated environments
• Excellent communication; able to explain trade-offs to engineers and executives alike
• Legally entitled to work in Canada

Nice to have

• Databricks Certified Data Engineer Professional or Solutions Architect credential; Azure or AWS architect certification
• Lakeflow / Delta Live Tables, Delta Sharing and Lakehouse Federation
• Apache Iceberg interoperability and open table format strategy
• MLOps and GenAI on Databricks (MLflow, Model Serving, Vector Search, Mosaic AI)
• Terraform for Databricks and cloud infrastructure
• Experience in Life Sciences (GxP, clinical or commercial data) or Financial Services (risk, payments, regulatory reporting)
• Consulting or client-facing architecture background

Tech stack

• Platform: Databricks (Unity Catalog, Workflows, Databricks SQL, serverless)
• Storage & formats: Delta Lake, Apache Iceberg, Parquet
• Cloud: Azure (ADLS Gen2) or AWS (S3)
• Languages: Python (PySpark), SQL, Scala (a plus)
• Ingestion & streaming: Kafka / Event Hubs, Auto Loader, CDC tools
• Transformation: Spark, Lakeflow / Delta Live Tables, dbt
• ML & AI: MLflow, Model Serving, Vector Search
• DevOps: Git, CI/CD pipelines, Terraform, Databricks Asset Bundles
• Consumption: Power BI, Tableau, Databricks SQL

Why Augmented

Augmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.

• Shape the data platform strategy for a major enterprise client
• Small, senior teams with direct access to client decision-makers
• Exposure to AI-native delivery practices and modern tooling
• Compensation: [salary range to confirm] plus benefits

How to apply

Apply through this posting with your resume and a short note on a data lake or lakehouse you architected (scale, stack, your role).

Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.