search Browse Jobs
Sr. Forward Deployed Engineer (FDE) - Financial ServicesDatabricks · Central - United States
Databricks logo

Databricks

company page ↗ Visa Sponsoring Company

Sr. Forward Deployed Engineer (FDE) - Financial Services

✓ This company has sponsored visas before. The posting doesn't say so, but it's still worth applying.

🗓️ Posted 2026-09-02 Central - United States Hybrid ICT
💰 Salary Not shared 📊 Market ₹14,000–₹20,833/mo

About the Company

Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 - rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog. --- Databricks applicants Please apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool). Software Development Specialties: Apache Spark, Apache Spark Training, Cloud Computing, Big Data, Data Science, Delta Lake, Data Lakehouse, MLflow, Machine Learning, Data Engineering, Data Warehousing, Data Streaming, Open Source, Generative AI, Artificial Intelligence, Data Intelligence, Data Management, Data Goverance, Generative AI, AI/ML Ops

About the Role

As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & 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. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

Responsibilities

  • ● Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom 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.
  • ● 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.

Requirements

  • ● 6+ years experience in data engineering, data platforms & analytics, or software engineering.
  • ● Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks.
  • ● Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
  • ● Deep experience with distributed computing 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.
  • ● 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, translating complex concepts into actionable s.