Vacancy caducado!
1750 Tysons (12023), United States of America, McLean, Virginia
Distinguished Engineer - Data ArchitectAt Capital One, we believe in the values of excellence and doing the right thing. We are a technology-oriented company delivering financial products to market through modern technology and constant innovation at a massive scale.Distinguished Engineers are- Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices
- Visionaries, collaborating on Capital One's toughest issues, to deliver on business needs that directly impact the lives of our customers and associates
- Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community
- Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities
- Leaders who gain the trust and confidence of those around them, from hands on engineers to executives
- Innovative practices to bring data from producer to consumer and solving our most critical business problems in batch and real-time, making our most important customer decisions and driving our most critical data processes
- Demonstrates the highest level of hands on development and big picture architecture; able to mentor engineers and educate executives
- Design and develop cutting-edge solutions, using existing and emerging technology platforms
- Leverage sound judgment and problem solving to tackle some of Capital One's most critical problems and connect the dots to broader implications of the work
- Provide technical vision, technical solutions and directions to build complex and sustainable data ecosystem / platform
- Lead, manage and grow our data ingestion, data refinement and data consumption teams as an individual contributor/SME
- Design, develop, deploy and manage a highly reliable and scalable data pipeline
- Build/Modernize our data refinement/ETL processes
- Oversee the implementation of solutions for tracking data quality, data consistency and lineage.
- Embrace and incubate emerging technology and open source products across all platforms
- Collaborate with enterprise teams on developing and adhering to the company standards in terms of validation rules, nomenclature, design and deployments.
- Develop, demonstrate, and advocate data strategy at all levels from new engineers to senior executives
- Collaborate with internal teams to find areas of opportunities for automation and machine learning.
- Streamline the entire data ecosystem from end to end to ensure the most efficient , standard, privacy compliant processes possible.
- Establish best practices for data access that consider real-time and batch, security practices, and performance
- Show expertise for data at all levels: low-latency, relational, and unstructured data stores; analytical and ata lakes; data streaming (consumption/production), data in-transit
- 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
- Build awareness, increase knowledge and drive adoption of modern technologies and architecture patterns, sharing customer and engineering benefits to gain buy-in (working closely with leaders, other SMEs, and engineers)
- 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 (balance being a great coach and listener)
- Promote a culture of engineering excellence and being well-managed, using opportunities to reuse and innersource solutions where possible (always consider resiliency and impact; major focus on customer experience)
- 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 integrated manner
- Bachelor's Degree
- At least 7 years of experience in database management and data warehousing
- At least 5 years of experience developing in Python, Java, or Scala
- At least 5 years of Data Architecture and Data Modeling experience
- At least 5 years of experience working with Big Data
- At least 3 years of experience building real-time data products
- At least 3 years of experience working with Cloud technologies
- Masters' Degree
- 10+ years experience architecting and delivering software systems or platforms
- 10+ years of data governance, data access, data lineage, data monitoring, and security controls experience
- 4+ years of experience with AWS including EMR
- 4+ years experience working with Docker
- 3+ years of experience developing in Spark or Flink
- 3+ years of experience developing enterprise data models
- 3+ years of experience bringing real-time decision use cases to production
- 2+ years of experience building and managing Kubernetes
- 2+ years of experience building machine learning platforms and use cases
Vacancy caducado!