Process
Speak to a recruiter, then a coding exam that determines if you pass or fail, then a panel review.
The coding exam is on a platform that allows you to do practice exams, but the questions are very academically focused and verbose. This was not what I considered a fair test of coding skills for professionals.
Questions
What is your experience with Python?
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Interview Statistics
The following metrics were computed from 40 interview experiences for the Capital One Data Engineer role in United States.
Success Rate
35%
Pass Rate
Capital One's interview process for their Data Engineer roles in the United States is fairly selective, failing a large portion of engineers who go through it.
Experience Rating
Positive45%
Neutral23%
Negative33%
Candidates reported having good feelings for Capital One's Data Engineer interview process in United States.
Capital One Work Experiences
3.0
Flexible Hours, Bad Pay
Data Engineer • Current Employee
Bengaluru, Karnataka, India
June 4, 2025
Pros: Hybrid model and flexible hours
Cons: Poor compensation and benefits. No value for experienced [employees].
2.0
A Good Manager Is Essential
Data Engineer • Current Employee
Boston, Massachusetts, United States
February 14, 2024
Pros: Great pay and benefits.
A productive environment.
Lots of technical opportunities to build applications and tools.
Great time off policies.
Cons: Being productive is not enough; you have to play politics, and this makes your manager and skip-level manager essential for your growth.
4.0
Innovate, Learn, But Fast-paced
Data Engineer • Current Employee
Philadelphia, Pennsylvania, United States
February 28, 2025
Pros: Strong focus on innovation and technology in data engineering.
Opportunity to work with cutting-edge cloud and big data technologies (AWS, Snowflake, Apache Spark, Kafka).
Collaborative work environment with cross-functional teams.
Exposure to large-scale data processing and real-time analytics.
Emphasis on career growth, upskilling, and certifications.
Cons: Fast-paced environment with tight deadlines.
High expectations and performance pressure.
Complex organizational structure may slow down decision-making.
Frequent process changes requiring quick adaptability.
Workload can be demanding at times, depending on project timelines.
- 3.0Flexible Hours, Bad PayData Engineer • Current EmployeeBengaluru, Karnataka, IndiaJune 4, 2025Pros: Hybrid model and flexible hoursCons: Poor compensation and benefits. No value for experienced [employees].
- 2.0A Good Manager Is EssentialData Engineer • Current EmployeeBoston, Massachusetts, United StatesFebruary 14, 2024Pros: Great pay and benefits. A productive environment. Lots of technical opportunities to build applications and tools. Great time off policies.Cons: Being productive is not enough; you have to play politics, and this makes your manager and skip-level manager essential for your growth.
- 4.0Innovate, Learn, But Fast-pacedData Engineer • Current EmployeePhiladelphia, Pennsylvania, United StatesFebruary 28, 2025Pros: Strong focus on innovation and technology in data engineering. Opportunity to work with cutting-edge cloud and big data technologies (AWS, Snowflake, Apache Spark, Kafka). Collaborative work environment with cross-functional teams. Exposure to large-scale data processing and real-time analytics. Emphasis on career growth, upskilling, and certifications.Cons: Fast-paced environment with tight deadlines. High expectations and performance pressure. Complex organizational structure may slow down decision-making. Frequent process changes requiring quick adaptability. Workload can be demanding at times, depending on project timelines.
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