Senior Databricks Solutions Architect

Senior Databricks Solutions Architect - Detalhes da Vaga. ● This opportunity is not currently tied to a specific project. ● Selected professionals will complete the qualification process and may be matched with future Databricks projects according to their expertise, availability, project scope, and duration. ●Engagements are contractor/freelance and typically part-time, depending on project requirements. ●Important: Joining the talent pool does not guarantee an immediate project assignment. ●Key Responsibilities:Design scalable enterprise data solutions using Databricks and Apache Spark. ●Provide hands-on architecture and technical guidance across Databricks implementations. ●Support the design and delivery of production-grade Databricks solutions across multiple cloud environments. ●Lead or participate in architecture discussions, technical discovery sessions, and solution design activities with clients. ●Advise on Databricks performance optimization, scalability, governance, and platform best practices. ●Support CI/CD, production deployment, and MLOps practices within Databricks environments. ●Collaborate with client stakeholders, architects, and engineering teams throughout project engagements. ●Participate in technical assessments and the Databricks vetting process required for the DPP talent pool. ●Required Qualifications:7+ years of experience in Data Engineering, Data Platforms, and Analytics. ●10+ years of consulting experience. ●Experience delivering 6–8+ Databricks projects with hands-on development responsibilities. ●Databricks Data Engineering Professional certification and required Databricks training completed. ●Advanced knowledge of distributed computing with Apache Spark, including Spark runtime internals. ●Experience across at least two cloud ecosystems (AWS, Azure, GCP), with deep expertise in at least one. ●Strong understanding of the Databricks platform, performance optimization, scalability, and production architecture. ●Familiarity with CI/CD pipelines and production deployments. ●Working knowledge of MLOps practices. ●AI/GenAI knowledge is considered a plus, not a requirement. ●Key Screening Filters Before Submission:7+ years Data Engineering / Data Platforms / Analytics. ●10+ years consulting experience. ●6–8+ hands-on Databricks projects. ●Databricks Data Engineering Professional certification + required training. ●Advanced Spark / distributed computing knowledge. ●Experience with at least 2 clouds. ●CI/CD + production deployments. ●Working MLOps knowledge. ●Strong client-facing / consulting capabilities. ●Engagement Model:Freelancer talent pool / project-based / typically part-time. ●There is currently no specific project or guaranteed immediate assignment. ●. Requisitos para participar do processo. ● . O que oferecemos.