Staff Forward Deployed Engineer
Databricks3 months ago
Remote, IndiaStaff+
Responsibilities
- Collaborate on customer big data projects by creating reference architectures, how-to guides, and production-ready scalable tools and technologies.
- Advise strategic customers on big data transformations, third-party migrations, and the design, build, and deployment of big data and AI applications.
- Provide architecture and design expertise to support customer projects and successful Databricks adoption and integration.
- Partner with Engineering and Customer Support to provide feedback, resolve engagement-specific issues, and drive product improvements.
- Manage and guide multiple customer projects while maintaining architectural quality, proactively mitigating risks, and building customer trust.
Requirements
- 15+ years of experience with big data technologies such as Apache Spark, Kafka, cloud-native platforms, and data lakes in a customer-facing post-sales, technical architecture, or consulting role.
- 6+ years of independent experience working on big data architectures.
- 2+ years of experience working on AI-based implementations, including RAG, MCP, and context engineering.
- Strong experience with the Databricks ecosystem and the ability to code in Python or Scala.
- Experience working across GCP, AWS, and Azure.
- Ability to document and whiteboard technical solutions and apply strong problem-solving and critical-thinking skills.
- Experience supporting the deployment and integration of Databricks-based solutions for customer projects.
- Strong stakeholder-management skills and the ability to collaborate with technical and domain experts.
Benefits
- Comprehensive employee benefits and perks, with details varying by region.
Tech Stack
Categories
Forward Deployed
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.