- 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 .
- Strong 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.
- Solid 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)
🏢 TechDoQuest
📍 Toronto