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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Solutions Architect - **Company:** Frame Data AI, Inc. - **Location:** Houston, TX, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Computerized Maintenance Management Systems, Continuous Integration, Information Engineering, Data Governance, Data Integration, Python (Programming Language), Machine Learning, Operational Databases, Cloud Services, Search Technologies, SQL Databases, Data Streaming, Software Technical Review, Feature Engineering, Retrieval-Augmented Generation, Apache Spark, Generative AI, Data Lakes, Infrastructure Automation Frameworks, Machine Learning Operations, Virtual Agents, Data Pipelines, Serverless Computing, Databricks - **Published:** August 23, 2026 - **Apply:** https://www.disabledperson.com/jobs/74455572-solutions-architect ## About the Role 3-5 years, * 3-5 years of progressive experience in data engineering, cloud data platforms, or solution architecture, including at least 2 years of hands-on Databricks experience. * Databricks Certified Data Engineer Associate or Databricks Certified Data Engineer Professional certification required at the time of hire. * At least 1 year of hands-on experience with Databricks' newer platform capabilities, including Lakeflow Declarative Pipelines, Lakeflow Connect, Unity Catalog, serverless compute and SQL warehouses, Mosaic AI (Model Serving, Vector Search, and Agent Framework), AI/BI Genie, Databricks Apps, and/or Lakebase. * Strong hands-on proficiency with Python, SQL, Apache Spark, Delta Lake, and production data pipeline development. * Demonstrated experience designing secure cloud architectures, including identity, networking, access controls, secrets, data governance, and environment strategy. * Experience with CI/CD, infrastructure as code, automated testing, monitoring, and production support for Databricks solutions. * Ability to create clear architecture diagrams and communicate technical decisions to both engineering teams and business stakeholders. * Prior consulting or client-facing delivery experience, with the judgment to balance speed, quality, cost, and maintainability., * Databricks Certified Data Engineer Professional, Machine Learning Professional, or Databricks Certified Generative AI Engineer Associate certification. * Microsoft Azure architecture or data engineering certification. * Experience with ERP, EAM, CMMS, IoT, historian, OT, or other industrial data sources. * Experience in energy, industrial, manufacturing, utilities, or similarly operationally critical environments. * Working knowledge of MLflow, feature engineering, retrieval-augmented generation, agentic AI, or AI application architecture. * Experience estimating and leading small delivery teams through architecture, build, deployment, and transition to support. ## Description * Design Databricks lakehouse architectures across Azure, AWS, and/or GCP, with Azure experience strongly preferred. * Lead solution design for batch, streaming, data integration, analytics, AI, and operational use cases. * Define platform patterns for workspaces, networking, identity, security, environment separation, deployment, observability, and cost management. * Design governed data products and Medallion architectures using Delta Lake and Unity Catalog. * Guide engineering teams through implementation, conduct design and code reviews, and resolve complex technical issues. * Build or oversee production pipelines using SQL, Python, Spark, Lakeflow, Workflows, and cloud-native services. * Develop estimates, delivery approaches, architecture diagrams, technical roadmaps, and implementation plans. * Facilitate client workshops and explain architecture decisions, tradeoffs, risks, and recommendations to technical and executive stakeholders. * Support pre-sales discovery, solution shaping, demonstrations, and proposal development. * Contribute reusable patterns, accelerators, and standards to Frame's Databricks practice., * Architectures are pragmatic, secure, cost-aware, and implementable by the delivery team. * Clients understand the recommended approach and trust the technical decisions behind it. * Engineering teams have clear patterns, guardrails, and hands-on leadership that improve delivery quality. * Solutions move from design into production and create measurable operational or business value. ## Related Videos - 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