The posting, in Databricks's own words
archived Sep 10, 2026FEQ327R528 As a Specialist Solutions Architect (SSA), you will guide customers in building big data solutions on Databricks that span a large variety of use cases. These are customer-facing roles, working with and supporting the Solution Architects, requiring hands-on production experience with cloud infrastructure and big data technologies. SSAs help customers through the design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of the Databricks Data Intelligence Platform. As a deep go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs to continuously consolidate the skills in your area of speciality.
The impact you will have:
Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural and security design to development and deployment best practices including automation Architect production-level workloads, including end-to-end pipeline load performance testing and optimisation Provide technical expertise in cloud infrastructure and security relating to our Databricks Intelligence Platform Assist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, workload sizing, and custom architectures Improve community adoption (through tutorials, training, hackathons, conference presentations) Contribute to the Databricks Community and act as a technical SME.
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What we look for:
Pre-sales or post-sales experience working with external clients across a variety of industry markets Experience as a Data Platform engineer designing, setting up, and maintaining production-grade big data systems (Spark) Experience designing cloud infrastructure and services, such as AWS, Azure, or GCP, applying best practices in cloud security and networking, including: Designing, deploying, and maintaining cloud networks and connectivity (VPC/VNet design, routing, segmentation, private connectivity). Architect production cloud networks for data and AI workloads, including segmentation and routing, data exfiltration prevention, and performance/reliability Identity & Access Management (e.g. role-based access control, using the principle of least privilege, integration with IdPs, etc) Hands-on experience with cloud infrastructure automation (e.g. or cloud-specific resource management tools like ARM, CloudFormation, etc). Experience supporting customers in designing and implementing a security lakehouse/security data platform on Databricks to augment SIEM, enable security analytics and threat hunting, and build advanced detections. Ability to design and extend highly performant, scalable, secure, and cost-effective cloud-based big data solutions Deep knowledge of development tools and best practices for engineers including , unit and integration testing, plus automation and orchestration Production programming experience in one or more of the following languages - Python, Scala, SQL, or R Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent work experience The role located in Singapore covers the Asean and Greater China Regions, which requires travel up to 30% when needed. Nice to have: Databricks Certification About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .