Data Engineer 4, Python/AWS

Capital One

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

Posted 9/30/2026full-timeUnited StatesMid-LevelSenior💰 $179,400 - $225,100 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. Proficient in building scalable data pipelines and applying data security standards while collaborating effectively across Agile teams.

Highest-signal resume keywords

Python DevelopmentSQL ProficiencyData Pipeline DesignCloud Data SolutionsAgile Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Application DevelopmentData ModelingData EngineeringMachine LearningDistributed MicroservicesData WarehousingData Security StandardsData Pipeline DevelopmentRelational DatabasesNoSQL Databases

Soft Skills

CollaborationMentoringCommunication

Tools & Technologies

DatabricksSnowflakeSparkAWSMicrosoft AzureGoogle CloudEMRGlueAirflowMonte Carlo

Industry Keywords

Cloud Data ArchitectureData TrendsData SolutionsData PipelinesAgile Methodology

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureCassandraCloudDynamoDBJavaMicroservicesMongoDBNoSQLPythonScalaSparkSplunkSQL

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 warehouses 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 robust cloud-first data solutions
Independently design, build, and deliver cloud data solutions and applications
Architect and enforce common data-engineering design patterns across data 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
Implement data-security standards including encryption and fine-grained access control

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 4 years of experience in application development; internship experience does not apply
At least 2 years of experience in distributed data
At least 2 years of experience with SQL
At least 2 years of experience with Python, Java, or Scala
At least 2 years of experience in data pipeline design and development
At least 1 year of experience in data modeling and designing end-to-end data solutions using relational and non-relational database systems
No employer immigration sponsorship or immigration-related support available for a new applicant
Preferred: 7+ years of application development experience with Python, SQL, Scala, or Java
Preferred: 4+ years designing, deploying, and operating data workloads in a public cloud environment (AWS, Microsoft Azure, or Google Cloud)
Preferred: 4+ years building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
Preferred: 4+ years designing, implementing, and operating real-time or streaming data pipelines
Preferred: 2+ years with data observability or orchestration tools such as Monte Carlo, Splunk, Airflow, or Dagster
Preferred: 4+ years working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB
Preferred: 4+ years designing and supporting data warehousing solutions such as Snowflake or Redshift
Preferred: 2+ years in an Agile development environment
Preferred: 2+ years developing user-centric reusable data products

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonuses 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