Sr. Solutions Engineer (Data & AI)

Location: Singapore

Company

Databricks is a data and AI company providing a unified platform for data engineering, analytics, machine learning, and AI applications.

What you will do

• Lead technical discovery and solution design for customer workloads across data engineering, analytics, and machine learning.
• Build and deliver proofs-of-concept, live demos, notebooks, solution accelerators, and reference architectures on the Databricks Platform.
• Own frontline technical relationships with customer engineers, data teams, and technical leads.
• Develop account-level technical strategies with Account Executives to expand platform usage and consumption.
• Explain Databricks differentiation through hands-on demonstrations and competitive technical positioning.

Requirements

• 4+ years of experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting.
• Proficiency in Python and SQL, including debugging, optimization, and production-quality coding; live coding is required during the interview.
• Hands-on experience designing and implementing data solutions on AWS, Azure, or GCP.
• Working knowledge of distributed data systems such as Apache Spark, Delta Lake, Hadoop, Kafka, or Flink.
• Experience leading technical customer conversations, including discovery, whiteboarding, and architecture reviews.
• 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 or AI company, cloud provider, or technical consulting firm.

Culture & Benefits

• Comprehensive benefits and perks are provided, with details varying by region.
• Inclusive workplace committed to equal employment opportunity and diversity.
• Databricks operates 30+ offices around the globe and serves more than 20,000 organizations.

Hiring process

• Recruiter screen followed by a hiring manager screen.
• Design and architecture interview, live coding assessment, and build-demo-pitch presentation.
• Reference check.