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Capital One
Capital One
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Capital One is a financial services and fintech company offering credit cards, auto loans, banking, and savings products. Its work combines financial expertise with technology and digital tools to improve how customers manage money. The company’s careers focus includes building customer-oriented solutions within a diverse and inclusive workforce.
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Data Engineer 4, Python, AWS and Spark — Capital One, New York City

Full-time onsite Data Engineer role at Capital One, developing secure cloud-first and streaming data platforms for personalized marketing experiences. Work with Python, Spark, Kafka, SQL, Snowflake, and Databricks to build lakehouse solutions.

USUnited StatesNYNew YorkVAVirginia
$179,400 – $245,600 / year
On-siteFull-timeMiddleSeniorEnglish RequiredData Engineer
Amazon RedshiftAWSAzureCassandraCloudDynamoDBGoogle Cloud PlatformHadoopJavaKafkaLinuxMapReduceMongoDBNoSQLPythonRDBMSScalaShell ScriptingSparkSQLUnix

Description

  • Design, develop, test, and deploy resilient, scalable cloud-first data solutions, lakehouse architectures, and real-time streaming pipelines independently
  • Lead and influence cross-functional Agile teams spanning development, data analysis, and data science
  • Apply shared data engineering patterns that improve code quality, maintainability, and operational efficiency
  • Develop with Python, SQL, Scala, Spark, NoSQL databases, open-source relational databases, Databricks, and Snowflake
  • Implement encryption in transit and at rest, fine-grained access controls, data quality measures, governance, and permissible-use standards
  • Collaborate with digital product managers and software engineers to deliver reliable solutions and improve customer experiences
  • Explain technical concepts and data findings to both technical and non-technical stakeholders
  • Track technology developments, contribute to engineering communities, and use interactive AI tools to accelerate delivery
  • Conduct unit tests and peer reviews of code
  • Improve system performance, observability, and support for downstream consumers
  • Build scalable platforms for personalized omnichannel messaging and experiences across owned and paid advertising technology channels

Requirements

  • Bachelor’s degree or higher in computer science or a related quantitative field such as statistics, economics, operations research, analytics, mathematics, or engineering
  • At least four years of application development experience, excluding internships
  • At least two years of experience working with distributed data
  • At least two years of SQL experience
  • At least two years of experience with Python, Java, or Scala
  • At least two years of experience designing and developing data pipelines
  • At least one year of experience modeling data and designing end-to-end solutions with relational and non-relational databases
  • New applicants are not eligible for employer immigration sponsorship or immigration-related support
  • Preferred: Master’s degree in computer science, data engineering, information systems, or a related technical discipline
  • Preferred: Seven or more years of application development using Python, SQL, Spark, Scala, or Java
  • Preferred: Four or more years designing, deploying, and operating public-cloud data workloads on AWS, Azure, or GCP
  • Preferred: Four or more years building distributed data or computing workloads with EMR, Spark, AWS Glue, Databricks, MapReduce, Hadoop, or Hive
  • Preferred: Four or more years designing, implementing, and operating real-time streaming applications such as Kafka
  • Preferred: Four or more years designing and managing data warehouses such as Snowflake or Redshift
  • Preferred: Four or more years implementing NoSQL systems and semi-structured data solutions with MongoDB, Cassandra, or DynamoDB
  • Preferred: Four or more years working in UNIX or Linux environments with basic commands and shell scripting
  • Preferred: Two or more years using data orchestration or data observability tools
  • Preferred: Two or more years developing reusable, user-focused data products
  • Preferred: Two or more years working in Agile engineering and delivery environments
  • Preferred: Practical experience with interactive AI tools such as Claude Code or GitHub Copilot

Benefits

  • Performance-based incentive compensation may include cash bonuses and/or long-term incentives
  • Comprehensive, competitive, and inclusive health, financial, and other benefits supporting overall well-being
  • Reasonable accommodations are available for applicants who need them
  • Commitment to equal opportunity and nondiscrimination
  • Drug-free workplace

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