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Data Engineer 5 – Cloud Operations Resilience Engineering
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 data solutions, utilizing Python, SQL, and various database systems. Proven ability to lead data engineering initiatives, mentor teams, and communicate complex technical concepts effectively.
Highest-signal resume keywords
Cloud Data Solutions DesignPython ProgrammingData Pipeline DevelopmentSQL ProficiencyData Modeling Experience
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 Data SystemsMachine LearningMicroservices ArchitectureData 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 EngineeringCloud SolutionsData TrendsData ObservabilityStreaming Data Pipelines
Tech Stack
Tools & technologiesAWSAzureCloudJavaMicroservicesNoSQLPythonScalaSnowflakeSparkSQL
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 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 reusable data engineering design patterns
- 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 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
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
- 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 experience with proficiency in 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 bonuses and/or long-term incentives (LTI)
- Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being
- Reasonable accommodations for applicants with disabilities