Databricks Architect

About us:

Intuitive.AI is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solution and services companies supporting enterprise customers on a global scale. Intuitive is an "Engineering Company" delivering measurable value and key business outcomes.

Intuitive Superpowers:

• DataOps & AI/ML

• Cloud Native, AppSecOps, DevSecOps

• Cloud Migration & Transformation

• Cloud FinOps

• Cybersecurity (App/Data/Infra) & GRC

• SDx & Digital Workspace

We are proud to partner with some of the world's leading enterprises and serve 200+ customers across different industry verticals. We have achieved many milestones along the way, including being recognized as a top-10 fast-growth 150 IT company in the Americas by CRN in 2022 and being named one of America's fastest-growing private companies by INC 5000 in 2022. That’s not all! Even CIO Review awarded us as the Most Promising Cloud Migration Company and Artificial Intelligence Solutions Provider in 2022.

About the job:

Job Title: Databricks Architect

Location: Remote across Canada

Position Type: Full Time

We are seeking an experienced Databricks Architect with strong hands-on expertise in Unity Catalog, Apache Spark, PySpark, SQL, and Delta Lake. The ideal candidate will design, develop, and optimize scalable data engineering solutions on the Databricks Lakehouse platform while ensuring strong data governance, security, and access controls through Unity Catalog.

Key Responsibilities

• Design and develop scalable data pipelines using Databricks, Apache Spark, PySpark, and SQL.
• Build and optimize ETL/ELT pipelines using Delta Lake and Delta Tables.
• Implement and manage Unity Catalog across Databricks environments.
• Configure and manage Catalogs, Schemas, Tables, Views, External Locations, and Storage Credentials.
• Implement data access controls, RBAC, permissions, and governance policies using Unity Catalog.
• Support data lineage, auditing, data discovery, and governance requirements.
• Design and maintain secure data lakehouse architectures across cloud environments.
• Develop Databricks Jobs, Workflows, notebooks, and production-grade data pipelines.
• Optimize Spark jobs, SQL queries, Delta tables, and overall pipeline performance.
• Implement data quality, validation, monitoring, and error-handling frameworks.
• Work with cloud storage platforms such as Azure Data Lake Storage, Amazon S3, or Google Cloud Storage.
• Integrate Databricks with enterprise data platforms, databases, APIs, and downstream applications.
• Implement CI/CD processes for Databricks development and deployment.
• Use Git, Terraform, or Databricks Asset Bundles for infrastructure and deployment automation.
• Troubleshoot production data pipelines and resolve performance and data-quality issues.
• Collaborate with Data Architects, Cloud Engineers, Data Scientists, Business Analysts, and application teams.

Required Skills & Experience

• 5+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Strong experience implementing and working with Unity Catalog.
• Advanced PySpark and Apache Spark skills.
• Strong SQL development and query optimization experience.
• Hands-on experience with Delta Lake / Delta Tables.
• Experience building enterprise-grade ETL/ELT data pipelines.
• Experience with data governance, security, access management, and data lineage.
• Experience with at least one major cloud platform: Azure, AWS, or GCP.
• Strong understanding of Lakehouse architecture and modern data platforms.
• Experience with Databricks Workflows/Jobs and production deployments.
• Experience with Git and CI/CD.
• Good understanding of data modeling and performance optimization.

Preferred Skills

• Experience with Terraform or Databricks Asset Bundles.
• Experience with Azure Data Lake Storage, Amazon S3, or Google Cloud Storage.
• Experience with Azure Data Factory, AWS Glue, Airflow, or similar orchestration tools.
• Experience implementing Unity Catalog migration from legacy Hive Metastore.
• Experience with row-level and column-level security.
• Experience with Dynamic Views and fine-grained data access.
• Experience with Databricks SQL and SQL Warehouses.
• Experience with Delta Live Tables / Lakeflow Declarative Pipelines.
• Experience with CI/CD automation for Databricks.
• Knowledge of data privacy and compliance requirements.