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Data Engineer 5 (Python, SQL, Databricks, Snowflake) (Enterprise Platforms Technology)

Capital One · Chicago, IL · Full time

Posted Oct 1, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about the most complex data platform you designed. What would you change now?

What they are checking: Whether they can reflect on past architecture choices with honesty and growth.

How do you influence a group of engineers, analysts and data scientists to adopt a new standard?

What they are checking: Whether they lead through influence and clear reasoning, which a senior level demands.

Describe how you mentor other data engineers.

What they are checking: Whether they help others grow, which this role names as part of the job.

What would you do

A critical pipeline fails every few nights and nobody knows why. How do you investigate?

What they are checking: Whether they can debug systematically and improve observability.

How do you evaluate a new data technology before bringing it into a bank?

What they are checking: Whether they test new tools carefully against security, cost and support needs.

A product manager asks for a real-time feature that would require a major redesign. How do you respond?

What they are checking: Whether they explain trade-offs clearly and propose practical options.

About the work

When would you choose Databricks over Snowflake for a workload, or the other way around?

What they are checking: Whether they understand the strengths of each platform from real use, not marketing.

How do you design a lakehouse so data is reliable, discoverable and governed across many teams?

What they are checking: Whether they think about catalog, lineage and access controls at enterprise scale.

How do you optimize cost on a large cloud data platform?

What they are checking: Whether they consider storage, compute sizing and query efficiency to control spending.

How do you handle schema changes in upstream sources without breaking downstream consumers?

What they are checking: Whether they use contracts, versioning and testing to protect users of the data.

Practice this interview out loud.

Offer builds a real interview for this exact role at Capital One from your resume and this job description, asks the questions one at a time, and tells you what landed. The first one is free.

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The full job description

As published by Capital One.

Data Engineer 5 (Python, SQL, Databricks, Snowflake) (Enterprise Platforms Technology) Position Overview We are seeking a Data Engineer to develop the technical vision, architectural design, and implementation of our AI-enabling data ecosystem. In this strategic role, you will bridge the gap between traditional enterprise data architecture and modern AI capabilities. You will design resilient, scalable data pipelines, and real-time streaming architectures that power LLM workflows, Retrieval-Augmented Generation (RAG) pipelines, and predictive ML models. You will work closely with Data Scientists, Analysts, and other Engineers to establish best-in-class data engineering practices for traditional and AI enabled workloads. About the Team The Enterprise Platforms Tech Top of House Data & Analytics team serves as the strategic intelligence backbone for executive leadership and strategy. We operate at the intersection of business strategy, core enterprise infrastructure, and advanced analytics. Our team is responsible for delivering high-impact, enterprise-level data products, decisioning engines, and modern analytics capabilities that power executive level decision-making. Key Responsibilities • AI Architecture & Data Foundation: Architect, build, and scale clean, reliable, and latency-optimized data pipelines (batch and real-time) designed specifically to supply structured, semi-structured, and unstructured data to AI/ML applications and Large Language Models (LLMs). • Technical Leadership & Strategy: Contribute to defining the architectural blueprint for the Top of House AI data layer. Serve as a hands-on technical lead, guiding junior and mid-level engineers in coding standards, design patterns, and engineering excellence. • Data Governance, Security, & Lineage: Partner with Enterprise Security and Data Governance teams to implement robust data classification, privacy safeguards, and automated lineage tracking for AI models and training datasets. • Feature Engineering & Store: Build and maintain scalable feature stores to support both real-time inferencing and offline model training across executive-facing predictive models. • Performance & Cost Optimization: Audit and optimize cross-cloud data pipelines, query performance, and storage infrastructure for efficiency, cost management, and reliability. • Cross-Functional Collaboration: Partner directly with Technical Program Managers, Data Scientists, Top of House leads, and C-suite stakeholders to turn executive data needs into production-ready solutions. Basic Qualifications: • Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) • At least 6 years of experience in application development (Internship experience does not apply) • At least 4 years of experience in distributed data • At least 4 years of experience with SQL • At least 4 years of experience programming with at least one of the following languages: Python, Java, or Scala • At least 4 years of experience designing and developing data pipelines • At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems Preferred Qualifications: • Master's Degree in a related field • 9+ years of experience in application development including Python, SQL, Scala, or Java • 5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) • 5+ year experience working on real-time data and streaming applications • 5+ years of data warehousing experience (eg Snowflake) • Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion (Claude, Gemini) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $209,000 - $238,500 for Data Engineer 5 McLean, VA: $229,900 - $262,400 for Data Engineer 5 New York, NY: $250,800 - $286,200 for Data Engineer 5 Plano, TX: $209,000 - $238,500 for Data Engineer 5 Richmond, VA: $209,000 - $238,500 for Data Engineer 5 San Francisco, CA: $250,800 - $286,200 for Data Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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