Databricks Solutions Architect

Role: Databricks Solutions ArchitectLocation: Remote Mandatory: Databricks Certification Job SummaryWe are seeking a hands-on, customer-facing Resident Solutions Architect with deep Databricks Platform expertise, combined with strong CI/CD and Terraform skills. This is an architect-level role for someone who can work directly with enterprise clients, design scalable Lakehouse and data platform solutions, and stay hands-on through build, deployment, and production support — including infrastructure-as-code delivery of the Databricks platform itself.Key ResponsibilitiesServe as a resident, customer-facing Databricks Solutions Architect, providing architectural guidance, best practices, and hands-on delivery for enterprise Lakehouse implementations.Design and implement scalable Lakehouse architectures using PySpark, Spark SQL, and Delta Lake.Own Unity Catalog governance and security design, including data access controls, lineage, and cross-workspace governance patterns.Build and operate production data pipelines using Delta Live Tables (DLT) and Databricks Workflows.Administer Databricks Workspaces and Accounts, including provisioning, access management, and platform configuration.Provision and manage Databricks infrastructure using Terraform, including workspace, cluster, Unity Catalog, and job/workflow resources as reusable, version-controlled modules.Design and implement CI/CD pipelines for Databricks assets (notebooks, DLT pipelines, jobs, ML models) using GitHub Actions, GitLab CI, Jenkins, Azure DevOps, or equivalent, including Databricks Asset Bundles.Perform Spark performance tuning — partitioning, caching, Adaptive Query Execution (AQE), and data skew mitigation — to optimize cost and performance at scale.Design and manage SQL Warehouses for BI and analytics workloads.Build streaming data solutions using Kafka and Structured Streaming.Architect Databricks solutions across AWS, Azure, or GCP, tailored to each cloud's native services and security model.Partner directly with client engineers, business stakeholders, and executives to translate business problems into Databricks/Lakehouse solutions and measurable outcomes.Guide client teams through migration from legacy ETL platforms (e.g., Informatica) to Databricks.Required Skills15+ years of experience in Data Engineering, Cloud Engineering, Solutions Architecture, or Platform Engineering.Databricks Certification required (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Solutions Architect, or equivalent).5+ years of hands-on Databricks Platform experience, including:PySpark, Spark SQL, and Delta LakeLakehouse Architecture design and implementationUnity Catalog governance and securityDelta Live Tables (DLT)Databricks WorkflowsWorkspace and Account AdministrationSQL WarehousesStrong hands-on Terraform experience with Databricks, including reusable modules for workspace, cluster, and Unity Catalog provisioning.Strong CI/CD experience (GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, or equivalent), including CI/CD for Databricks Asset Bundles, notebooks, and jobs.Strong Spark performance tuning expertise — partitioning, caching, AQE, and data skew resolution.Kafka and Structured Streaming experience.Strong experience with AWS, Azure, or GCP.Proven customer-facing experience providing architectural guidance and Databricks best practices to enterprise clients.Strong communication and stakeholder-management skills, with the ability to translate business needs into practical Lakehouse solutions.Preferred SkillsMLflow for model tracking and lifecycle management.Databricks AI capabilities (AI/BI, Databricks Assistant, Mosaic AI).Experience migrating legacy ETL platforms (e.g., Informatica) to Databricks.Familiarity with the latest Databricks features — Genie, Lakebase, and Databricks Apps.Experience working with enterprise clients in a consulting or professional-services environment.Kubernetes, Docker, and cloud-native application architecture.