> Markdown version of [/jobs/ext/4286492-databricks-architect](https://www.wearedevelopers.com/jobs/ext/4286492-databricks-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Architect - **Company:** Rapid Eagle Inc. - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Salary:** $145,600.0 - $176,800.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Software Design Patterns, Python (Programming Language), Performance Tuning, SQL Databases, Google Cloud, Cloud Platform System, System Availability, Apache Spark, Data Lakes, Data Lakehouse, Databricks - **Published:** October 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2b016cba3340abcf ## About the Role * 5+ years of experience in data architecture, data engineering, or a related field * Hands-on expertise with Databricks, Apache Spark, and Delta Lake * Proficiency in Python, Scala, or SQL for large-scale data processing * Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform * Strong understanding of data lakehouse, data warehouse, and ETL/ELT design patterns * Databricks Certified Associate or Professional certification is a plus * Excellent communication skills with the ability to translate complex technical concepts to stakeholders ## Description * Design, build, and optimize enterprise-scale Databricks and data lakehouse architectures * Develop and maintain data pipelines using Apache Spark, Delta Lake, and related technologies * Collaborate with data engineers, analysts, and business stakeholders to define technical requirements * Establish best practices for data governance, security, and performance tuning within Databricks * Lead cloud data platform integrations across AWS, Azure, or GCP environments * Provide technical guidance and mentorship to junior data engineering team members * Monitor, troubleshoot, and continuously improve platform reliability and efficiency