Databricks Architect

Intuitive Technology Partners Inc
United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Airflow Amazon Web Services Amazon S3 Microsoft Azure Cloud Computing Cloud Storage Databases Continuous Integration Data Architecture Data Discovery Information Engineering
+27 more
Data Governance Data Infrastructure Extract Transform Load (ETL) Data Security Apache Hive Identity and Access Management Operational Databases Performance Tuning Query Optimization Role-Based Access Control Azure Data Lake Software Deployment SQL Databases Workflow Management Systems Enterprise Data Management Google Cloud Azure Data Factory Apache Spark Git Data Lakes Pyspark Data Lineage Deployment Automation AWS Glue Terraform Data Pipelines Databricks

Job description

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., * 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.

Requirements

  • 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 Google Cloud Platform.
  • 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.

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