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Capital One

Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)

Boston, MA, United States

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Job details

Posting language: English
Posted: Nov 3, 2026

Original job description

Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)

Job Description

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Data Engineers who are passionate about marrying data with emerging technologies. In this role, you’ll be at the forefront of driving a major transformation across Capital One.

What You’ll Do:

Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
Influence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Utilize programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and Snowflake
Share your passion for staying on top of trends in data, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the data community
Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
Independently design, build and deliver world-class cloud data solutions and applications with little or no support from supervisors or managers
Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelines
Serve as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alignment and shared understanding
Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, ensuring robust performance under increasing data volume and business demands
Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
Lead and execute large-scale, transformative data initiatives from end to end, independently driving critical architectural decisions and evaluating platform choices, such as Snowflake versus Databricks, based on technical and business requirements

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 Computer Science or a related field
8+ years of experience in data engineering
4+ years of data modeling experience
9+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java
5+ years of hands-on experience designing, deploying and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
5+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
5+ years of experience designing, implementing, and operating real-time or streaming data pipelines
3+ years of experience working on data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster)
5+ years of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
5+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
3+ years of experience working in an Agile development environment
3+ years of experience developing user-centric reusable data products

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.

Remote (Regardless of Location): $209,000 - $238,500 for Data Engineer 5

McLean, VA: $229,900 - $262,400 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 (https://www.capitalonecareers.com/benefits) . 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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More about this job

Skills

Full-stack development
Machine learning
Microservices
Programming languages
Python
Apache Spark
NoSQL
Data warehousing
Databricks
Snowflake
Coaching
Data engineering
Computer science
Statistics
Research
SQL
Oracle Java
Scala
Data modelling
Database management systems
AWS
Microsoft Azure
Google Cloud
EMR
Splunk
Apache Airflow
MongoDB
Apache Cassandra
Amazon DynamoDB
Amazon Redshift
Agile development
Technical support
Recruitment

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