About this role
Engineers who thrive at the intersection of client engagement and hands-on technical architecture will find a natural home in this role. Databricks is seeking a senior solutions engineer based in Singapore to independently guide technical evaluations and drive platform adoption across enterprise accounts. Working alongside account executives, the incoming practitioner will design data and machine learning solutions, build live demonstrations, and navigate complex competitive landscapes.
The daily routine involves leading discovery sessions with customer engineering teams, authoring production-quality code, and creating reusable reference architectures for the broader technical community. Success requires a blend of deep technical fluency in distributed systems and the communication skills needed to explain platform differentiation to technical leads. Individuals who enjoy coding complex data pipelines while simultaneously acting as trusted technical advisors to major enterprises will excel here.
What you will do
- Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning.
- Build and deliver proofs-of-concept and live demonstrations on the Databricks Platform to secure technical wins.
- Manage frontline technical relationships with customer engineers, data teams, and technical leads.
- Collaborate with account executives to develop technical strategies that grow platform consumption.
- Navigate competitive landscapes by articulating platform differentiation through hands-on technical demonstrations.
- Contribute reusable technical assets such as notebooks, solution accelerators, and reference architectures to the solutions architecture community.
What you need
- Bring at least four years of professional experience in data engineering, solutions architecture, technical pre-sales, or hands-on consulting.
- Demonstrate proficiency in Python and SQL with the ability to write, debug, and optimize production-quality code.
- Possess hands-on experience designing and implementing data solutions on at least one major public cloud platform including AWS, Azure, or GCP.
- Show working knowledge of distributed data systems such as Apache Spark, Delta Lake, Hadoop, Kafka, or Flink.
- Display a history of leading technical customer conversations covering discovery, whiteboarding, and architecture reviews.
- Hold a bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent practical experience.
Nice to have
- Databricks certification or prior 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
Skills and tech stack
Questions candidates ask
Where is this job located?
This position is located in Singapore.
What does the interview process look like?
The evaluation pipeline starts with a recruiter screen, followed by a hiring manager screen, a design and architecture interview, a live coding assessment, and concludes with a build, demo, pitch presentation and reference check.
What technologies will I be expected to know?
Candidates must be proficient in Python and SQL, have experience with at least one public cloud platform like AWS, Azure, or GCP, and understand distributed data systems such as Apache Spark or Delta Lake.