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Data Engineer 4, Python, AWS, SQL, GenAI
Capital One. Collaborate across 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-based data solutions, utilizing Python, SQL, and data pipeline development. Proficient in architecting scalable data systems and enforcing data engineering best practices while collaborating effectively across Agile teams.
Highest-signal resume keywords
Python DevelopmentSQL ProficiencyData Pipeline DesignCloud Data SolutionsData Engineering Best Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Application DevelopmentData ModelingDistributed Data SystemsRelational DatabasesNoSQL DatabasesData WarehousingMachine LearningData Security StandardsData Pipeline DevelopmentData Observability
Soft Skills
CollaborationMentoringCommunication
Tools & Technologies
SparkDatabricksSnowflakeEMRGlueCloud Platforms
Certifications & Qualifications
Bachelor's Degree in Computer Science
Industry Keywords
Agile DevelopmentLakehouse ArchitectureFull-Stack SystemsStreaming Data PipelinesUser-Centric Data Products
Tech Stack
Tools & technologiesCloudJavaMicroservicesNoSQLPythonScalaSparkSQL
About the role
Key responsibilities & impact- Collaborate across Agile teams to design, develop, test, implement, and support 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
- 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 cloud-first data solutions
- Independently design, build, and deliver cloud data solutions and applications
- Architect and enforce data engineering design patterns for code 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
- 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 experience in application development; internship experience does not apply
- At least 2 years of experience in distributed data
- At least 2 years of experience with SQL
- 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 designing end-to-end data solutions using relational and non-relational database systems
- No employer-sponsored immigration support or work authorization sponsorship for new applicants
- Preferred: 7+ years of application development experience
- Preferred: 4+ years designing, deploying, and operating data workloads in a public cloud environment
- 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 orchestration tools
- Preferred: 4+ years with unstructured or semistructured data using NoSQL databases
- Preferred: 4+ years designing and supporting data warehousing solutions
- Preferred: 2+ years in an Agile development environment
- Preferred: 2+ years developing user-centric reusable data products
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 who require them