Sr. Solutions Engineer
Databricks10 hours ago
Singapore, SingaporeSenior
Responsibilities
- Lead technical discovery and solution design for customer workloads involving data engineering, analytics, and machine learning.
- Build and deliver proofs of concept, live demonstrations, 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.
- Explain Databricks differentiation through hands-on demonstrations and contribute reusable technical assets to the solutions architect community.
Requirements
- At least 3 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 part of 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.
- Familiarity with data engineering, data science and machine learning, MLOps, or SQL analytics.
- Strong presentation and live demonstration skills.
- Bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
- Databricks certification or Databricks Platform experience is preferred, as is experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow.
Benefits
- Databricks offers comprehensive benefits and perks, with region-specific details provided through its benefits information.
Tech Stack
Apache FlinkApache HadoopApache KafkaApache SparkAWSAzureDatabricksGoogle Cloud PlatformMLflowPythonSQL
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.