Data Engineer

Capital One

. Collaborate across Agile teams to design, develop, test, implement, and support technical solutions .

Posted 11/5/2026full-timeUnited StatesMid-LevelSenior💰 $209,000 - $286,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing cloud-based data solutions using Python, SQL, and distributed data technologies. Proven ability to lead data engineering initiatives, mentor team members, and communicate complex technical concepts effectively.

Highest-signal resume keywords

Python ProgrammingData Pipeline DevelopmentCloud Data SolutionsData ModelingAgile Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonJavaScalaData EngineeringData WarehousingData Pipeline DesignMachine LearningDistributed MicroservicesNoSQL Databases

Soft Skills

CollaborationMentoringCommunicationInfluencingProblem-Solving

Tools & Technologies

DatabricksSnowflakeAWSMicrosoft AzureGoogle CloudSparkEMRGlueMongoDBCassandra

Industry Keywords

Data EngineeringCloud ComputingAgile MethodologyData ArchitectureData Observability

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureCassandraCloudDynamoDBJavaMicroservicesMongoDBNoSQLPythonScalaSnowflakeSparkSQL

About the role

Key responsibilities & impact

Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Use Python and Spark, relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and Snowflake
Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data community members
Collaborate with product managers and software engineers to deliver cloud-first data solutions
Independently design, build, and deliver cloud data solutions and applications
Architect and enforce data engineering design patterns across platforms and pipelines
Communicate technical concepts and data outcomes to internal and external stakeholders
Design and build scalable, resilient, and operationally efficient data pipelines and platforms
Mentor peers and junior engineers while contributing hands-on technical expertise
Lead large-scale data initiatives end to end, making architectural decisions and evaluating platform choices such as Snowflake versus Databricks

Requirements

What you’ll need

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 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 relational and non-relational database systems
Preferred: Master’s Degree in Computer Science or a related field
Preferred: 8+ years of experience in data engineering
Preferred: 4+ years of data modeling experience
Preferred: 9+ years of experience in application development with proficiency in Python, SQL, Scala, or Java
Preferred: 5+ years of experience designing, deploying and operating data workloads in AWS, Microsoft Azure, or Google Cloud
Preferred: 5+ years of experience building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
Preferred: 5+ years of experience designing, implementing, and operating real-time or streaming data pipelines
Preferred: 3+ years of experience with data observability or data orchestration tools
Preferred: 5+ years of experience with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB
Preferred: 5+ years of experience designing and supporting data warehousing solutions such as Snowflake or Redshift
Preferred: 3+ years of experience in an Agile development environment
Preferred: 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

Benefits

Comp & perks

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial and other benefits supporting total well-being
Employment authorization sponsorship consideration for a new qualified applicant
Reasonable accommodations for applicants who require them