Senior Data Engineer – Risk Tech

Capital One

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

Posted 9/24/2026full-timeMcLean • Virginia • United StatesSenior💰 $209,000 - $262,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable cloud data solutions, leveraging Python, SQL, and various database systems. Proven ability to lead data engineering initiatives, mentor team members, and communicate complex technical concepts effectively.

Highest-signal resume keywords

Python ProgrammingSQL DevelopmentData Pipeline DesignCloud Data SolutionsData Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Application DevelopmentData ModelingDistributed DataMachine LearningData WarehousingNoSQL DatabasesRelational DatabasesData Engineering Design PatternsStreaming PipelinesData Observability

Soft Skills

CollaborationMentoringCommunication

Tools & Technologies

DatabricksSnowflakeCloud-Based Data WarehousingAgile Development

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science (Preferred)

Industry Keywords

Risk ManagementLakehouse ArchitectureMicroservicesData SolutionsData Pipelines

Tech Stack

Tools & technologies

CloudJavaMicroservicesNoSQLPythonScalaSparkSQL

About the role

Key responsibilities & impact

Collaborate across Agile teams to design, develop, test, implement, and support full-stack 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, relational and NoSQL databases, Databricks, Snowflake, and cloud-based data warehousing platforms
Build and deploy proprietary AI-powered risk-management solutions with the GRC team and company partners
Design, build, and deliver scalable cloud data solutions and applications independently
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
Mentor peers and junior engineers while contributing hands-on technical expertise
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 programming experience 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: Experience with public cloud environments, distributed data workloads, streaming pipelines, data observability/orchestration, NoSQL databases, data warehousing, Agile development, and 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 bonuses and/or long-term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being
Reasonable accommodations for applicants who require them
Equal opportunity and non-discrimination protections