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Capital One

Data Engineer 5 – Enterprise Platforms Technology

Capital One

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

Posted 9/22/2026full-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 data solutions using Python, SQL, and distributed data technologies. Proven ability to lead data engineering initiatives, mentor teams, and communicate complex technical concepts effectively.

Highest-signal resume keywords
Python ProgrammingSQL DevelopmentData Pipeline DesignCloud Data SolutionsData Engineering Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Application DevelopmentData ModelingDistributed Data SystemsMachine LearningData WarehousingNoSQL DatabasesReal-Time Data PipelinesData Engineering Design PatternsAgile DevelopmentData Observability
Soft Skills
CollaborationMentoringCommunication
Tools & Technologies
DatabricksSnowflakeAWSMicrosoft AzureGoogle CloudSparkEMRGlueMongoDBCassandra
Industry Keywords
Cloud Data WarehousingLakehouse ArchitectureData TrendsData SolutionsData Pipelines

Tech Stack

Tools & technologies
Amazon RedshiftAWSAzureCassandraCloudDynamoDBJavaMicroservicesMongoDBNoSQLPythonScalaSparkSQL

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, open-source relational and NoSQL databases, and cloud data warehousing platforms including Databricks and Snowflake
  • Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data professionals
  • 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 common 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 and innovation
  • 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 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
  • Reasonable accommodations for applicants with disabilities