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Capital One
Capital One
H1B Visa SponsorBankingFinanceFintech
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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Senior Data Engineer 4 – Python, AWS, Spark, Kafka | Capital One, New York

Build cloud-first lakehouse and streaming data platforms at Capital One. Help deliver personalized omnichannel marketing experiences for millions of customers.

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

Description

  • Design, develop, test, and deploy resilient cloud-first data solutions, lakehouse architectures, and real-time streaming pipelines independently.
  • Guide cross-functional Agile teams that include developers, data analysts, and data scientists.
  • Apply consistent data engineering patterns to improve code quality, maintainability, and operational efficiency.
  • Develop with Python, SQL, Scala, Spark, NoSQL databases, open-source relational databases, Databricks, and Snowflake.
  • Implement encryption, fine-grained access controls, data quality practices, governance, and permissible-use standards.
  • Work with digital product managers and software engineers to deliver reliable solutions and improve customer experiences.
  • Explain technical concepts and data insights to both technical and non-technical stakeholders.
  • Engage with engineering communities, track technology developments, and use interactive AI tools to accelerate delivery.
  • Conduct unit testing and peer reviews while optimizing performance, observability, and downstream usability.
  • Create scalable platforms for hyper-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 discipline, 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.
  • This role does not provide employer sponsorship or immigration-related employment authorization 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 data workloads in 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 or streaming applications such as Kafka.
  • Preferred: Four or more years designing and managing Snowflake or Redshift warehouses and data models.
  • 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 observability tools such as Airflow, Dagster, Monte Carlo, or Splunk.
  • Preferred: Two or more years developing reusable, user-focused data products.
  • Preferred: Two or more years working in Agile engineering and delivery environments.
  • Preferred: Hands-on 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 benefits across health, financial well-being, and other areas of total wellness.
  • Reasonable accommodations are available for applicants with disabilities.

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