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MF
Lead Hand - Warehouse
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- Full-time
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MF
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AI
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MM
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SD
Senior Project Manager
Symbiotic Digital
ON · Downtown Toronto (Central Bay Street), Ontario
- Contract

Tredence Inc.

Azure Databricks Architect

Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Nov 2, 2026

Original job description

We are seeking an experienced and visionary Azure Databricks Architect to lead the design, implementation, and scaling of our enterprise data and AI platform. In this role, you will define the core architecture for our Lakehouse environment, champion governance standards using Databricks Unity Catalog, and spearhead end-to-end performance tuning and cost optimization initiatives. You will work closely with data engineering teams, cloud infrastructure teams, security officers, and business stakeholders to deliver a robust, secure, and high-performance data ecosystem.

Key Responsibilities

Lakehouse Architecture & Design

Design and implement enterprise-grade Lakehouse architectures using Azure Databricks and Delta Lake, following Medallion Architecture (Bronze, Silver, Gold layers).
Architect secure, scalable, and highly available cloud data pipelines supporting batch and real-time streaming workloads.
Integrate Azure Databricks seamlessly with the broader Azure ecosystem (e.g., Azure Data Lake Storage Gen2, Azure Data Factory, Microsoft Entra ID, and Azure Monitor).

Data Governance & Security (Unity Catalog)

Design, deploy, and manage Databricks Unity Catalog for centralized metadata management, data discovery, and lineage tracking across multi-workspace environments.
Implement fine-grained access controls (RBAC/ABAC), row-level security (RLS), and column-level masking (CLM) to protect sensitive assets (PII/PHI).
Establish auditing procedures, data sharing frameworks, and compliance guardrails using Unity Catalog audit logs.

Performance Tuning & Cost Optimization

Drive Databricks and Spark optimization strategies, including managing shuffle partitions, resolving data skew, tuning cache, and applying Adaptive Query Execution (AQE).
Implement layout strategies such as Z-ordering, data compaction (OPTIMIZE), and vacuum scheduling to curtail I/O overhead and boost query performance.
Optimize cluster configurations, autoscaling parameters, spot instances, and serverless compute pools to maximize cost efficiency without compromising SLAs

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More about this job

Responsibilities

Design and scale an enterprise Azure Databricks Lakehouse platform, including secure batch and streaming pipelines integrated with Azure services. Lead Unity Catalog governance and security, and optimize Spark performance, cluster configurations, and platform costs.

Requirements

The role calls for mid-to-senior-level expertise in Azure Databricks, Lakehouse architecture, Delta Lake, Unity Catalog, and the Azure ecosystem. It also requires the ability to implement data governance and security controls and tune Spark workloads and cloud resources for performance and cost efficiency.

Skills

Azure Databricks
Lakehouse Architecture
Delta Lake
Medallion Architecture
Databricks Unity Catalog
Data Governance
Data Security
RBAC/ABAC
Row-Level Security
Column-Level Masking
Apache Spark Optimization
Adaptive Query Execution
Z-Ordering
Azure Data Lake Storage Gen2
Azure Data Factory
Cost Optimization

Visa sponsorship

Not detected in the job text

Keywords

Azure Databricks
Lakehouse
Delta Lake
Medallion Architecture
Bronze Layer
Silver Layer
Gold Layer
Batch Processing
Real-Time Streaming
Azure Data Lake Storage Gen2
Azure Data Factory
Microsoft Entra ID
Azure Monitor
Databricks Unity Catalog
Metadata Management
Data Discovery
Data Lineage
RBAC
ABAC
Row-Level Security
Column-Level Masking
PII
PHI
Audit Logs
Apache Spark
Shuffle Partitions
Data Skew
Adaptive Query Execution
Z-Ordering
OPTIMIZE

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