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Data Engineer
Capital One. Collaborate with Agile teams to design, develop, test, implement, and support technical solutions .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing cloud data solutions, with a strong focus on data engineering, data modeling, and building scalable data pipelines. Proficient in Python, SQL, and distributed data technologies, while effectively mentoring and collaborating with cross-functional teams.
Highest-signal resume keywords
Cloud Data Solutions DesignData EngineeringPython ProgrammingSQL ProficiencyData Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLJavaScalaData Pipeline DevelopmentData ModelingDistributed DataMachine LearningMicroservicesData Warehousing
Soft Skills
CollaborationMentoringCommunicationInfluencingProblem Solving
Tools & Technologies
DatabricksSnowflakeAWSMicrosoft AzureGoogle CloudSparkEMRGlueAgile DevelopmentData Orchestration Tools
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science
Industry Keywords
Data EngineeringData SolutionsCloud ComputingData TrendsData Observability
Tech Stack
Tools & technologiesAWSAzureCloudJavaMicroservicesNoSQLPythonScalaSparkSQL
About the role
Key responsibilities & impact- Collaborate with Agile teams to design, develop, test, implement, and support technical solutions
- Influence developers, data analysts, and data scientists across machine learning, distributed microservices, lakehouse architecture, and full-stack systems
- Use Python, Spark, relational and NoSQL databases, Databricks, and Snowflake
- Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data professionals
- Collaborate with product managers and software engineers to deliver cloud-first data solutions
- Independently design, build, and deliver cloud data solutions and applications
- Architect and enforce data engineering design patterns for quality, maintainability, and reusability
- 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 innovation
- Lead large-scale data initiatives end to end, making architectural decisions and evaluating platforms such as Snowflake and 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 experience programming 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
- Capital One will consider sponsoring a new qualified applicant for employment authorization
- Preferred: Master's Degree in Computer Science or a related field
- Preferred: 8+ years of experience in data engineering
- Preferred: 4+ years of data modeling experience
- Preferred: 9+ years of application development with Python, SQL, Scala, or Java
- Preferred: 5+ years designing, deploying and operating data workloads in AWS, Microsoft Azure, or Google Cloud
- Preferred: 5+ years building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
- Preferred: 5+ years designing, implementing, and operating real-time or streaming data pipelines
- Preferred: 3+ years working on data observability or data orchestration tools
- Preferred: 5+ years working with unstructured or semistructured data using NoSQL databases
- Preferred: 5+ years designing and supporting data warehousing solutions
- Preferred: 3+ years working in an Agile development environment
- Preferred: 3+ years developing user-centric reusable data products
Benefits
Comp & perks- Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
- Comprehensive health, financial and other benefits supporting total well-being
- Equal opportunity and non-discrimination protections
- Reasonable accommodations for applicants with disabilities