These two companies have rapidly growing FDE programs. Here is what their interviews look like.

Databricks - Field Engineering / Solutions Architect

Interview Process (4-5 rounds):

1. Recruiter Screen - Background, motivation, role fit
2. Technical Screen - SQL, Python, data engineering concepts
3. System Design - Design a data pipeline or lakehouse architecture
4. Customer Scenario - Role-play a client interaction. They give you a messy business problem and you need to propose a Databricks-based solution
5. Behavioral / Values - Culture fit, collaboration examples

Key Focus Areas:

• Spark and distributed computing concepts
• SQL fluency - they will test complex queries
• Data lakehouse architecture
• Ability to simplify complex technical concepts
• Experience with messy, real-world data problems

Tips:

• Learn Databricks products deeply - Unity Catalog, Delta Lake, MLflow
• Practice explaining data concepts to a non-technical audience
• Prepare examples of debugging data quality issues

Scale AI - Forward Deployed Engineer

Interview Process (4-5 rounds):

1. Recruiter Screen - Motivation and background
2. Coding Round - Python-heavy, practical problems (not leetcode hard)
3. System Design - Design a data labeling pipeline or ML workflow
4. Case Study - Given a customer scenario, propose an end-to-end solution
5. Cross-functional - Work with a PM or non-technical stakeholder in a simulated meeting

Key Focus Areas:

• Python proficiency
• Understanding of ML/AI workflows
• Data quality and labeling concepts
• Client communication skills
• Ability to work under ambiguity

Tips:

• Understand the AI data supply chain - labeling, quality, evaluation
• Read about Scale's products (Data Engine, GenAI Platform)
• Practice rapid prototyping - they value speed of execution
• Show you can context-switch between technical and business conversations

Have you interviewed at either company? Share details to help others prepare.