Databricks

✓ Verified Sponsor

Forward Deployed Engineer

🗓️ Posted 2026-09-02 Remote - India Hybrid ICT

Company shared salary

Market rate

₹450,000–₹800,000/mo (₹5,400,000–₹9,600,000/yr)

Based on similar roles (title + domain + location).

● Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom data applications and data ingestion and ML/AI model integration.
● Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading Big Data and AI applications, and work with engagement managers to scope technical delivery work with input from the customer.
● Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
● Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
● Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
● Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues.
● Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
● Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

● 6+ years of experience in data engineering, data platforms & analytics (additional software engineering experience is a nice-to-have).
● Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
● Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals.
● Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
● Familiarity with CI/CD for production deployments.
● Working knowledge of MLOps, ML/AI models and AI APIs.
● Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
● Experience with technical project delivery - managing scope, timelines and measurable outcomes.