Junior/Medior SAP/SAC Data Engineer at BAM working on SAP data transformation for analytics and reporting. Collaborating within a DevOps team to optimize data pipelines and reporting structures.
About the role
- Data Engineer at Capital One focusing on innovative technology solutions and mentoring talent. Collaborating on enterprise-wide initiatives and implementing cutting-edge practices.
Responsibilities
- Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
- Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team
- Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
- Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization
- Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner
- Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent
- Zero-Registration Observability: Implement an automated discovery framework for 100% systemic data flow visibility without manual registration.
- Deterministic Inference Engine: Engineer an SCA/AST-based inference engine to map data logic in imperative code for compliance-grade lineage.
- Data Passport Protocol: Define a cross-boundary protocol to embed immutable metadata for end-to-end traceability across external systems.
- Advanced Static Analysis: Develop language-agnostic parsers to interpret data flow intent from codebases without requiring execution.
- Autonomous Triage: Interface the DCG with AI agents via MCP to enable autonomous Root Cause Analysis and real-time failure remediation.
- Map Data Movement: Prototype infrastructure-level data interception using kernel-level tools to create a geographic map of enterprise data movement.
- Simplification & Governance: Consolidate fragmented metadata silos into a single queryable graph and automate capture to eliminate documentation overhead.
Requirements
- Bachelor’s Degree
- At least 9 years of experience in data engineering
- At least 5 years of experience in data architecture
- At least 3 years of experience building applications in AWS
- Masters’ Degree (Preferred)
- 10+ years of experience in data engineering (Preferred)
- 3+ years of data modeling experience (Preferred)
- 2+ years of experience with ontology standards for defining a domain (Preferred)
- 2+ years of experience using Python, SQL or Scala (Preferred)
- 1+ year of experience deploying machine learning models (Preferred)
- 3+ years of experience implementing big data processing solutions on AWS (Preferred)
Benefits
- Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
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