> Markdown version of [/jobs/ext/3867532-databricks-solution-architect-onsite-w2](https://www.wearedevelopers.com/jobs/ext/3867532-databricks-solution-architect-onsite-w2). 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 Solution Architect - Onsite- W2 - **Company:** CLOUDSCOUTS SOFTWARE SOLUTIONS LLC - **Location:** King of Prussia, PA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Unity 3d, Artificial Intelligence, Amazon Web Services, Amazon S3, User Authentication, Microsoft Azure, Cloud Computing, Cloud Computing Security, Cloud Engineering, Cloud Storage, Computer Programming, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Integration, Data Sharing, Data Warehousing, DevOps, Dimensional Modeling, Apache Hive, Identity and Access Management, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Power BI, Azure Machine Learning, Azure Data Lake, Data Streaming, Tableau (Software), Google Cloud, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Generative AI, Infrastructure as Code (IaC), Data Lakes, Pyspark, Data Lineage, Deployment Automation, Apache Kafka, Data Management, Machine Learning Operations, Video Streaming, Terraform, Databricks - **Published:** October 22, 2026 - **Apply:** https://www.thejobnetwork.com/job/6e933cef-a409-4143-a6c4-4c58cfc9de9a/databricks-solution-architect-onsite-w ## About the Role 12+ years of experience in Data Engineering, Data Architecture, Cloud Architecture, or related fields. 5+ years of strong Databricks experience, including architecture and implementation. Strong hands-on experience with: Databricks Lakehouse Platform Apache Spark / PySpark Delta Lake Unity Catalog Databricks SQL Databricks Workflows / Jobs Delta Live Tables / Lakeflow Data governance and security Strong understanding of Data Lake, Data Warehouse, and Lakehouse architectures. Experience designing enterprise-scale batch and real-time/streaming data pipelines. Strong programming experience with Python and/or Scala. Strong SQL development and performance-tuning skills. Experience with at least one major cloud platform: AWS Microsoft Azure Google Cloud Platform Experience with cloud storage technologies such as Amazon S3, Azure Data Lake Storage, or Google Cloud Storage. Experience with Terraform/IaC and CI/CD. Strong understanding of networking, IAM, authentication, encryption, and cloud security. Excellent communication, presentation, documentation, and stakeholder-management skills. Preferred Skills Databricks certifications are highly preferred. Experience with MLflow, Model Serving, Mosaic AI, and Generative AI. Experience with LLM/RAG architectures and AI/ML platforms. Experience with Kafka or other event-streaming technologies. Experience with data integration tools such as Informatica, ADF, dbt, or equivalent. Experience with Power BI/Tableau and enterprise analytics architectures. Experience with enterprise data governance and compliance requirements. Experience leading architecture workshops and technical discussions with senior stakeholders. Strong understanding of data modeling, dimensional modeling, metadata management, data lineage, and master data concepts. ## Description We are looking for an experienced Databricks Solution Architect to design, architect, and lead the implementation of enterprise-scale data and AI solutions using the Databricks Data Intelligence Platform. The ideal candidate should have strong hands-on experience with Databricks, Lakehouse architecture, Apache Spark, Delta Lake, Unity Catalog, cloud platforms, data engineering, and modern data/AI architectures. The candidate will work closely with business stakeholders, data engineers, developers, cloud teams, and enterprise architects to translate business requirements into scalable, secure, high-performance Databricks solutions. Databricks' architecture guidance emphasizes Lakehouse architecture, governance, security, reliability, performance, cost optimization, and interoperability. Key Responsibilities Design and implement enterprise-grade Databricks Lakehouse architectures across development, testing, and production environments. Define target-state architecture for data engineering, analytics, BI, machine learning, and AI workloads. Architect solutions using Databricks, Delta Lake, Apache Spark, Unity Catalog, Databricks SQL, Workflows, and Lakehouse Federation. Design and implement enterprise data governance, security, access control, lineage, and data-sharing strategies using Unity Catalog. Lead migration of legacy data platforms, data warehouses, and Hive Metastore environments to Databricks/Unity Catalog. Develop scalable data ingestion and processing architectures for batch and streaming workloads. Provide technical leadership for performance tuning, scalability, reliability, and cost optimization of Databricks environments. Design cloud-native solutions leveraging AWS, Azure, or GCP and integrate Databricks with cloud storage, networking, security, and identity services. Establish Infrastructure as Code (IaC) and deployment strategies using Terraform and CI/CD. Databricks currently recommends Terraform for automating workspace, networking, storage, and Unity Catalog infrastructure. Collaborate with DevOps teams to implement automated deployment pipelines and environment promotion. Provide technical guidance to data engineers and development teams and conduct architecture/design reviews. Work directly with customers and stakeholders to understand requirements and present architecture options and recommendations. Create architecture diagrams, technical design documents, standards, and implementation roadmaps. Troubleshoot complex production issues and provide architectural recommendations for resolution. Stay current with emerging Databricks Data + AI capabilities, Generative AI, ML, and Lakehouse technologies.