Distinguished Engineer, Risk Management Data Architect

4 days ago

Washington, United States Capital One Full time
Distinguished Engineer, Risk Management Data Architect

Information Technology Management Professional Services

Job Description

Center 1 (19052), United States of America, McLean, Virginia. Capital One is looking for a Distinguished Engineer with extensive experience in data engineering, data architecture, and data modeling to drive the design and implementation of a high-performance data ecosystem that supports real-time, intelligent experiences to enable our Risk Management functions. In this role, you will help shape the Risk Management Data domains that will drive our journey towards standardized data assets and data products.

Distinguished Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next-generation technology solutions. This role is part of the Risk Technology organization. In Risk Technology, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data-driven tools that use machine learning to prevent risks & automatically detect issues before they impact our business, our customers, or our communities.

Key Responsibilities:
  1. Define and implement data architecture standards, frameworks, and guidelines to ensure data platform efficiency and to ensure high-quality data for gaining insights/downstream consumptions.
  2. Lead the creation of data models and ontologies to standardize data definitions, relationships, and semantics across systems.
  3. Collaborate with extended teams and stakeholders to establish data standards, metadata management practices, and data quality frameworks.
  4. Design scalable architectures that integrate various data sources, systems, and platforms while minimizing duplication.
  5. Partner with engineering, data analysis, data science, and business teams to align data solutions with business needs.
  6. Mentor technical teams in data architecture best practices.
  7. Develop comprehensive architectural documentation and communicate data architecture principles to both technical and non-technical stakeholders.
  8. Conduct exploratory data analysis to elucidate deficiencies and opportunities with tangible evidence.
  9. Partner with other Distinguished Engineers across the enterprise to identify and foster investments in shared data services and platforms.
  10. Engage with senior business product leads to understand the business strategy, value propositions, relative priorities, and criteria for success.
What skills do you need to have:
  1. Hands-on experience with AWS Cloud data technologies including RDS, DynamoDB, S3, and Glue ETL.
  2. Experience designing and implementing event-based stream processing solutions using technologies such as Kafka, Kinesis, Spark, and Flink.
  3. Ability to design and implement high availability, multi-region data replication for mission-critical applications.
  4. Experience designing and implementing data management solutions that enable Data Quality, Reference Data Management, and Metadata Management.
  5. A track record of designing and implementing end-to-end data pipelines supporting both production and analytic use cases.
  6. Comfortable coding with Python or Scala and proficient in SQL.
  7. In-depth understanding of AVRO, Parquet, and DeltaLake data formats.
  8. Background using multiple data storage technologies including relational, document, key/value, graph, and object stores.
  9. Demonstrated ability to partner with internal product and intent owners to help define requirements and outcomes for data-focused initiatives.
  10. Ability to decompose large problems and execute smaller, manageable bodies of work to demonstrate continuous architecture delivery.
  11. Understanding of machine learning and AI data infrastructure needs.
Basic Qualifications:
  1. Bachelor’s degree.
  2. At least 7 years of experience in Data Architecture and Data Engineering.
  3. At least 7 years of Data modeling and platform design.
  4. At least 2 years of experience in cloud computing (building applications in AWS).
Preferred Qualifications:
  1. Bachelor's or Master's Degree in Computer Science or a related field.
  2. At least 2 years of experience with ontology standards for defining a domain.
  3. At least 2 years of experience using Python, SQL, or Scala.
  4. At least 1 year of experience deploying machine learning models.
  5. Experience implementing knowledge graphs.
  6. Familiarity with Industry standards related to Data.
  7. Experience with data mesh, data lakehouse architectures, and real-time data pipelines.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

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