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

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.

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Data Lake Architect (Databricks)

Augmented