Req: FEQ427R137 Location: Singapore

The Role

As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.

The Impact You Will Have

• Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
• Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins
• Own frontline technical relationships with customer engineers, data teams, and technical leads
• Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption
• Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations
• Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community

What We Look For

• 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
• Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage
• Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
• Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
• Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
• Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
• Strong presentation and demo skills — you will build and present a live solution during the interview
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

• Databricks certification or experience with the Databricks Platform
• Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
• Background at a data/AI company, cloud provider, or technical consulting firm

Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check