Databricks Technical Architect

Tangentia; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Tangentia is seeking an experienced Databricks Technical Architect to design and implement scalable data and analytics solutions on the Databricks platform. You will lead architecture decisions, governance, and the optimization of data workloads across cloud environments to deliver robust, cost-efficient data platforms.

The role requires deep hands-on expertise with Databricks, Spark, PySpark, SQL, Delta Lake, and modern data architectures, plus strong stakeholder management to translate

Qualifications

• 8+ years of experience in Data Engineering/Data Architecture.
• Hands-on Databricks, Spark, PySpark, and SQL proficiency.
• Experience with Delta Lake and data lakehouse architecture.
• Cloud platform experience (Azure, AWS, or GCP) required.
• CI/CD and DevOps experience needed.

Responsibilities

• Design and implement enterprise-scale data platforms using Databricks.
• Define data architecture, governance, security, and best practices.
• Build and optimize ETL/ELT pipelines using Spark, PySpark, and SQL.
• Collaborate with business and technical stakeholders to deliver data solutions.
• Lead migration of legacy data platforms to Databricks and cloud environments.
• Provide technical leadership, solution design, and architecture guidance.
• Optimize performance, scalability, and cost efficiency of data workloads.

Skills

Databricks

Apache Spark

PySpark

SQL

Cloud platforms

Delta Lake

Data Governance

CI/CD

Stakeholder management

Solution architecture

Job description

Job Summary

We are seeking an experienced Databricks Technical Architect to design, architect, and implement scalable data and analytics solutions on the Databricks platform. The ideal candidate will have strong expertise in data engineering, cloud technologies, big data frameworks, and modern data architectures.

Key Responsibilities

• Design and implement enterprise-scale data platforms using Databricks.
• Define data architecture, governance, security, and best practices.
• Build and optimize ETL/ELT pipelines using Spark, PySpark, and SQL.
• Collaborate with business and technical stakeholders to deliver data solutions.
• Lead migration of legacy data platforms to Databricks and cloud environments.
• Provide technical leadership, solution design, and architecture guidance.
• Optimize performance, scalability, and cost efficiency of data workloads.

Required Skills

• 8+ years of experience in Data Engineering/Data Architecture.
• Strong hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
• Experience with Azure Databricks, AWS, or GCP cloud platforms.
• Knowledge of Delta Lake, Data Lakehouse architecture, and data governance.
• Experience with CI/CD, DevOps, and data integration tools.
• Strong stakeholder management and solution architecture skills.

Preferred Certifications

• Databricks Certified Data Engineer/Architect
• Azure Solutions Architect or relevant Cloud Certifications