Entry Level Data Infrastructure Engineer Jobs
New grad data infrastructure engineer jobs connect recent graduates and entry level candidates with 0 to 2 years of experience to their first professional role, where a strong portfolio or internship project often carries more weight than a lengthy resume. Most openings are on-site positions across Technology & Software, Retail, and E-Commerce & Online Marketplaces, with employers like Amazon, HeyGen, and OpenAI hiring at this level now.
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Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Business Cards and Payments (BC&P) Credit Infrastructure Team owns the end-to-end development of valuations models, monitoring, advanced analytics and systemized tooling for the Business Cards and Payments (BCP) organization. We are hiring a Data Scientist on the credit card acquisitions valuations model development team to empower credit programs in BCP through robust valuations models and tools that support use of those models.
In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals
The Ideal Candidate is:
Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Basic Qualifications:
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
At least 1 year of experience leveraging open source programming languages for large scale data analysis
At least 1 year of experience working with machine learning
At least 1 year of experience utilizing relational databases
Preferred Qualifications:
PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
At least 4 years of experience in Python, Scala, or R for large scale data analysis
At least 4 years of experience with machine learning
At least 4 years of experience with SQL
At least 1 year of experience with people management or project management
At least 1 year of experience working with AWS
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.
McLean, VA: $197,300 - $225,100 for Mgr, Data Science
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.
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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Find JobsEntry Level Data Infrastructure Engineer Job Market
Who's Hiring
- Amazon9
- HeyGen1

- OpenAI1
- Capital One1
- ApisLogic1A
Top Industries Hiring
- Technology & Software12
- Retail9
- E-Commerce & Online Marketplaces9
- Artificial Intelligence1
- Banking & Financial Services1
Entry Level Data Infrastructure Engineer Jobs: Frequently Asked Questions
How do I get an entry level data infrastructure engineer job?
Entry level data infrastructure engineer roles typically look for hands-on proof of skill over credential length. Build a portfolio with projects that show you can design or automate pipelines, work with tools like Terraform, Kubernetes, or Apache Kafka, and manage cloud infrastructure on AWS, GCP, or Azure. Internship experience, open-source contributions, and relevant certifications all strengthen a first application.
Which companies hire entry level data infrastructure engineers?
Companies hiring entry level data infrastructure engineers right now include Amazon, HeyGen, and OpenAI, based on current listings on Migrate Mate as of July 2026. Both large tech organizations and fast-growing startups regularly open junior positions at this level, especially those scaling their data platforms or modernizing legacy infrastructure.
Are there remote entry level data infrastructure engineer jobs?
Yes, though remote availability at the entry level is more limited than at senior levels. About 0% of entry level data infrastructure engineer openings are remote or hybrid as of July 2026, so candidates open to hybrid or on-site arrangements will have access to a broader set of opportunities.
Are these new grad data infrastructure engineer jobs?
Yes, the listings on this page include new grad, recent graduate, and junior data infrastructure engineer roles. A posting is generally new-grad friendly when it welcomes 0 to 2 years of experience, counts internships or academic projects toward that threshold, or explicitly accepts a portfolio in place of prior full-time employment. Filtering for those signals helps narrow the list quickly.
Which industries hire the most entry level data infrastructure engineers?
Entry Level data infrastructure engineer roles concentrate in Technology & Software, Retail, and E-Commerce & Online Marketplaces, based on current listings on Migrate Mate as of July 2026. These sectors tend to drive junior hiring because they are actively building or scaling data platforms and need early-career engineers to support growing pipeline and cloud infrastructure workloads.