To succeed in the Milliman interview loop, you must demonstrate a balance of theoretical computer science knowledge and practical, hands-on data engineering capability.

Role-Related Knowledge – You must show a deep command of database engines, query optimization, and write clean, idiomatic Python. Your understanding of data structures, indexing, and distributed computing (like PySpark) should be practical, not just academic. Be ready to explain the trade-offs of the technologies you have used in past projects.

Problem-Solving & Logical Agility – Interviewers at Milliman place a premium on how you think. Whether you are writing a complex SQL query or solving a logical puzzle, they want to hear your thought process out loud. Break down complex requirements systematically, state your assumptions clearly, and validate your edge cases before declaring a solution complete.

Structural Code Design – Writing code that "just works" is not enough. You must write code that is modular, readable, and maintainable. Demonstrating a strong grasp of OOP principles and design patterns shows that you can contribute to their long-term, enterprise-grade codebases.

Communication and Domain Alignment – Milliman is a client-facing consulting and technology firm. You must be able to translate complex technical concepts into clear business impacts. Showing an interest in financial risk, actuarial concepts, or healthcare metrics will immediately differentiate you from other candidates.

The hiring process for a Data Engineer at Milliman is structured to thoroughly evaluate both your foundational technical capabilities and your analytical problem-solving skills. The process typically spans several weeks, and each round acts as a progressive filter.

Initially, the process begins with resume shortlisting, followed by an online aptitude and technical assessment. This initial test evaluates your logical reasoning, basic quantitative skills, and core programming fundamentals. Candidates who clear this threshold are contacted for an initial screening, which often includes a brief telephonic conversation focusing on basic SQL questions and your professional background.

Following the initial screen, you will enter the core technical evaluation phase. This consists of two to three intensive technical interviews. These rounds focus heavily on live coding, deep-dive database queries, Python fundamentals, and OOP concepts. You will also face logical puzzles designed to test your analytical thinking. The final stage is a managerial and HR round, which assesses your system design understanding, cultural fit, communication style, and alignment with the team's working dynamics.

The timeline above illustrates the standard progression from the initial online assessment through to the final managerial and HR evaluations. Most candidates find that the technical screens and live coding rounds require the highest concentration of preparation energy. While the process is rigorous, it is designed to ensure that you are fully prepared for the highly analytical environment at Milliman.

SQL & RDBMS Optimization

SQL is the lifeblood of Milliman’s data operations. You will be tested on your ability to write highly performant queries and your understanding of relational database management systems (RDBMS).

Be ready to go over:

• Query Optimization – How to read execution plans, utilize indexes (clustered vs. non-clustered), and avoid common pitfalls like table scans and unnecessary subqueries.
• Advanced Analytical Functions – Master window functions (ROW_NUMBER(), RANK(), DENSE_RANK(), LEAD(), LAG()) and complex aggregations using GROUP BY and HAVING.
• Database Design – Normalization forms, primary and foreign key relationships, and designing schemas that balance write efficiency with read performance.

Example scenarios:

• Optimizing a query that joins three massive tables containing financial transactions, policyholder details, and regional risk codes.
• Detecting and resolving a database deadlock scenario in a multi-threaded data ingestion pipeline.

Python & Object-Oriented Programming

You will need to demonstrate that you can write clean, production-ready Python code that adheres to industry-standard software engineering practices.