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Data Architecture Expert for Scalable Risk Management
1 week ago
At Capital One, we are seeking a highly skilled Data Architecture Expert to drive the design and implementation of a high-performance data ecosystem that supports real-time, intelligent experiences for our Risk Management functions. With extensive experience in data engineering, data architecture, and data modeling, you will play a crucial role in shaping the Risk Management Data domains that will drive our journey towards standardized data assets and data products.
A Distinguished Engineer with expertise in designing and implementing event-based stream processing solutions using technologies such as Kafka, Kinesis, Spark, and Flink will be responsible for defining and implementing data architecture standards, frameworks, and guidelines to ensure data platform efficiency and high-quality data for gaining insights/downstream consumptions. You will lead the creation of data models and ontologies to standardize data definitions, relationships, and semantics across systems.
This role requires collaboration with extended teams and stakeholders to establish data standards, metadata management practices, and data quality frameworks. You will design scalable architectures that integrate various data sources, systems, and platforms while minimizing duplication. Partnering with engineering, data analysis, data science, and business teams to align data solutions with business needs is also essential.
We offer a comprehensive compensation package, including an estimated salary of $274,800 - $313,600 for Distinguished Engineers in New York City (Hybrid On-Site). This role is also eligible to earn performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. In addition, you will enjoy a range of benefits, including health, financial, and other perks that support your total well-being.
To be successful in this role, you will need hands-on experience with AWS Cloud data technologies, including RDS, DynamoDB, S3, and Glue ETL. Experience designing and implementing data management solutions that enable Data Quality, Reference Data Management, and Metadata Management is also required. A track record of designing and implementing end-to-end data pipelines supporting both production and analytic use cases is essential.
Bachelor's degree or higher in Computer Science or a related field is preferred. At least 7 years of experience in Data Architecture and Data Engineering, 2 years of experience in cloud computing, and experience with ontology standards for defining a domain are also desired.