Senior Forward Deployed Engineer - Financial Services
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
About the Role
You will work directly with customers to build and productionize solutions to their data and AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. You will embed with customer teams, scope delivery work with engagement managers, and contribute reusable accelerators and frameworks.
Requirements
- 6+ years experience in data engineering, data platforms & analytics, or software engineering
- Comfortable writing code in Python, Scala, JavaScript/TypeScript and modern frameworks
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Deep experience with Apache Spark and knowledge of Spark runtime internals
- Familiarity with CI/CD for production deployments
- Working knowledge of MLOps, ML/AI models and AI APIs
- Experience designing and deploying production end-to-end data architectures and applications
- Experience with technical project delivery
- Documentation and white-boarding skills
- Experience working with enterprise clients and managing stakeholder conflicts
- Travel to customers 20% of the time
- Databricks Certification
Responsibilities
- Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion and ML/AI model integration
- Guide strategic customers through end-to-end design, build and deployment of big data and AI applications
- Scope technical delivery work with engagement managers and customer input
- Guide customers on architecture and design and drive adoption of Databricks
- Lead architecture and design decisions that are secure, scalable and aligned with best practices
- Collaborate with the Databricks technical team, Project Manager, Architect and customer team
- Provide product and implementation feedback to Engineering and Customer Support
- Embed with customer teams and engage stakeholders from technical ICs to executives
- Contribute accelerators, frameworks and best practices that influence the product roadmap
Benefits
- Annual performance bonus eligibility
- Equity eligibility