Design and architect enterprise-scale data platforms using Databricks Lakehouse architecture.
Lead data modernization initiatives including migration from legacy data warehouses to cloud-based platforms.
Define best practices for data ingestion, transformation, storage, and analytics using Databricks.
Implement and optimize Apache Spark, Delta Lake, and Unity Catalog .
Ensure data security, governance, metadata management, and compliance standards are met.
Collaborate with cloud, data engineering, analytics, and business stakeholders to translate requirements into technical solutions.
Provide architectural guidance, code reviews, and technical leadership to delivery teams.
Support CI/CD pipelines, automation, and infrastructure-as-code for data platforms.
Troubleshoot performance, scalability,



and cost optimization issues.

Required Skills & Qualifications
8+ years of experience in data engineering / data architecture / analytics platforms .
Robust hands-on experience with Databricks on Azure, AWS, or GCP .
Expertise in Apache Spark, PySpark, SQL , and data processing frameworks.
Experience with Delta Lake , data lakes, and data warehousing concepts.
Robust understanding of cloud architecture , networking, and security principles.
Knowledge of data governance, data quality, lineage, and compliance frameworks.
Excellent communication and stakeholder management skills.
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📌 Databricks Architect Toronto (Canada)
🏢 TechDoQuest
📍 Canada