About this role
Data architects and technical pre-sales professionals who enjoy guiding enterprise clients through complex data platform migrations will find a strong fit in this Singapore-based role. Databricks needs a technical strategist to lead architecture discussions, drive platform adoption, and act as a trusted advisor for customer engineering leads.
Working across data engineering, machine learning, and real-time analytics, the person in this position will own the technical direction for accounts from early discovery through production deployment. They will coordinate specialized teams, build custom solutions to win competitive scenarios, and shape product roadmaps by sharing customer feedback with internal engineering groups.
What you will do
- Manage the complete technical strategy for assigned accounts starting from initial discovery up to production deployment and consumption growth.
- Design scalable, production-grade solutions encompassing data engineering, machine learning, AI, and real-time analytics.
- Act as a trusted technical advisor to customer architects, engineering leads, and Directors.
- Drive technical wins in competitive scenarios by demonstrating platform differentiation through custom-built solutions.
- Develop and declare an emerging technical specialization to become a resource within the team for a specific domain.
- Coordinate cross-functional resources including data specialists, solution specialists, and partners to deliver comprehensive customer solutions.
- Influence product direction by providing structured feedback regarding customer requirements and competitive gaps.
What you need
- Bring five or more years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
- Demonstrate strong coding proficiency in Python and SQL through live coding, debugging, and solution-building skills.
- Possess deep expertise in distributed data systems architecture, including scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Show proficiency on the Databricks platform or a demonstrated ability to achieve proficiency rapidly with a developing technical specialization.
- Display a proven ability to lead architecture discussions with senior technical stakeholders using whiteboarding, design reviews, and trade-off analysis.
- Have experience with production deployments on public cloud providers like AWS, Azure, or GCP, covering infrastructure, security, and governance.
- Hold a Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent practical experience.
Nice to have
- Databricks certifications such as Data Engineer, ML, or Platform
- Experience with competitive platforms including Snowflake, AWS native services, or Azure Synapse
- Background in a data or AI company or a major cloud provider
- Industry domain expertise in sectors such as Financial Services, Healthcare, Retail, or Media
Skills and tech stack
Questions candidates ask
What technical skills are tested during the interview process?
Candidates must demonstrate strong coding proficiency in Python and SQL. The evaluation includes live coding assessments and a design and architecture interview.
What does the interview process look like?
The hiring pipeline starts with a recruiter screen followed by a hiring manager screen. Subsequent stages include a design and architecture interview, a live coding assessment, and a build, demo, and pitch presentation alongside a reference check.
What is the scope of the technical specialization required?
The role requires developing an emerging technical specialization or archetype in an area such as real-time streaming, machine learning, AI, data governance, or migrations. This specialization helps establish the candidate as a go-to resource within the team.