Data Engineer 4 – Risk Tech

Capital One

. Collaborate across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies .

Posted 9/21/2026full-timeMcLean • Virginia • United StatesMid-LevelSenior💰 $179,400 - $225,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in full-stack development, data pipeline design, and cloud-based data solutions, with a strong focus on Python, SQL, and data engineering best practices. Capable of collaborating across Agile teams and communicating complex technical concepts effectively to stakeholders.

Highest-signal resume keywords

Full-Stack DevelopmentData Pipeline DesignPython ProgrammingSQL ExperienceCloud Data Solutions

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSQLJavaScalaData Pipeline DesignData ModelingMachine LearningDistributed DataData Security StandardsData Engineering Design Patterns

Soft Skills

CollaborationMentoringCommunication

Tools & Technologies

DatabricksSnowflakeEMRSparkGlueAirflowMonte CarloSplunkLangChainLlamaIndex

Certifications & Qualifications

Bachelor's Degree in Computer ScienceRelated Quantitative Field

Industry Keywords

Agile DevelopmentCloud EnvironmentData WarehousingNoSQL DatabasesUnstructured Data

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureCassandraCloudDynamoDBJavaMicroservicesNoSQLPythonScalaSparkSplunkSQL

About the role

Key responsibilities & impact

Collaborate across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies
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 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 reusable 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
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 application development experience (internship experience does not apply)
At least 2 years of experience in distributed data
At least 2 years of SQL experience
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 end-to-end data solutions using relational and non-relational database systems
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 data orchestration tools such as Monte Carlo, Splunk, Airflow, or Dagster
Preferred: 4+ years with unstructured or semistructured data using NoSQL databases such as Mongo, 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
Experience with vector embeddings pipelines or vector search solutions
Experience designing data pipelines and context retrieval frameworks for LLM integrations using LangChain or LlamaIndex
Experience preparing unstructured text, logs, or document datasets for Generative AI workflows
Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI)
Comprehensive, competitive health, financial, and other benefits supporting total well-being
Reasonable accommodations for applicants with disabilities