Berkshire Hathaway Data Engineer Interview Experience (2026) — Conglomerate Analytics, 3 Rounds

I got the offer. Here's exactly what happened at Berkshire Hathaway's Data Engineer interview (Remote).

• Role: Data Engineer
• Location: Remote (Global)
• Year: 2026
• Timeline: 3 weeks, application to offer
• Rounds: Online Assessment → Technical Round → Managerial Round
• Difficulty: Medium — data pipeline and analytics infrastructure required
• Outcome: Offer accepted
• Compensation: $130,000 base + $20,000 bonus

Quick Stats

Applied through Berkshire Hathaway's careers portal in October 2026. A recruiter reached out within a few days. The process took about 3 weeks — typical for a conglomerate's data team. Being a global role, all rounds were virtual.

Round 1: Online Assessment

Format: 75-minute coding test Duration: 75 minutes What they were testing: Problem-solving, data engineering fundamentals, SQL Interviewer approach: Automated

The assessment had 3 coding problems. One was about implementing a data pipeline for financial data — fitting for Berkshire's diverse business. Another involved designing a data warehouse schema. The third was a standard DSA problem about data processing.

I think the financial data-specific problems made this assessment more relevant than generic coding tests. They clearly test for domain awareness in data engineering for conglomerates.

Round 2: Technical Round

Format: 60-minute video call with shared coding Interviewer: Senior Data Engineer Duration: 55 minutes What they were testing: Data engineering fundamentals, SQL/Python expertise, pipeline design Interviewer approach: Practical — focused on real Berkshire Hathaway problems

The interviewer started with a warm-up: "Tell me about a challenging data pipeline you've built." I talked about implementing a financial data processing pipeline at my previous company.

Then we moved to coding. The problem was: implement a simple ETL pipeline that can process data from multiple subsidiaries, transform it, and load it into a data warehouse. I had to handle data validation, transformation logic, and error handling.

I used Python with Apache Airflow and implemented modular DAGs for different data sources. The interviewer pushed me on edge cases — what about data quality issues? How do you handle schema changes across subsidiaries?

His exact words were something like, "How would you scale this to handle data from 50+ subsidiaries?" That's when I brought up distributed processing, partitioning strategies, and automated schema evolution. He seemed satisfied that I understood the scale challenges.

Round 3: Managerial Round

Format: 45-minute video call Interviewer: Engineering Manager Duration: 40 minutes What they were testing: Culture fit, problem-solving, Berkshire's values Interviewer approach: Behavioral — focused on long-term thinking and reliability

This round was about my experience working with diverse data sources, my approach to data quality, and my alignment with Berkshire's values. I shared examples of how I'd built reliable data pipelines at my previous company.

He also asked about my comfort with Berkshire's long-term investment philosophy — how do you approach data infrastructure for long-term value? I emphasized my focus on building reliable, scalable systems that can evolve over decades.

The Insider Section

Here's something most guides don't mention: Berkshire Hathaway puts a lot of emphasis on understanding their diverse business portfolio. In my technical round, they asked about handling data from different industries (insurance, railroads, utilities, retail). If you haven't studied conglomerate data challenges, you'll struggle.

Also, being a value-oriented conglomerate, they care deeply about data reliability and long-term thinking. The interviewer asked about data governance, audit trails, and maintaining data quality over decades. They're not just looking for technical skills — they want people who understand the importance of reliable data for long-term decision-making.

Compensation

The offer was $130,000 base with a $20,000 performance bonus. For a Data Engineer role in 2026, this is competitive for a conglomerate. The compensation grows significantly with experience and within the Berkshire ecosystem.

Honest Assessment

Who this role IS right for:

• Data engineers interested in diverse business domains
• People who value long-term thinking and reliability
• Those comfortable with working across different industries

Who this role IS NOT right for:

• Someone looking for rapid experimentation and fast iteration
• Engineers who don't care about data governance and long-term reliability
• People who prefer specialization over breadth

Frequently Asked Questions

How hard is the Berkshire Hathaway data engineer interview? Berkshire Hathaway's data engineer interview is moderately challenging — they test data engineering fundamentals, SQL/Python skills, and conglomerate data challenges. Less competitive than top tech companies but more diverse in scope.

How long does the Berkshire Hathaway interview process take? From application to offer, expect 2-4 weeks. Berkshire Hathaway's process includes technical rounds and can move quickly once they're interested.

What is the Berkshire Hathaway interview process and rounds? The process typically includes: Online Assessment (coding + data problems), Technical Round (data engineering + SQL), and Managerial Round. Some roles may have additional rounds.

How to prepare for Berkshire Hathaway data engineer interview in 2026-2027? Focus on data engineering fundamentals (SQL, Python, ETL), data pipeline design, and conglomerate data challenges (diverse industries, data governance). Understand Berkshire's business portfolio and long-term philosophy.

How much do data engineers make at Berkshire Hathaway? Data engineers at Berkshire Hathaway typically earn $110,000-$150,000 total compensation in 2026, depending on experience. Compensation grows with experience and within the Berkshire ecosystem.