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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.
Key Responsibilities:
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
Lead the creation of data models and ontologies to standardize data definitions, relationships and semantics across systems
Collaborate with extended teams and stakeholders to establish data standards, metadata management practices and data quality frameworks
Design scalable architectures that integrate various data sources, systems, and platforms while minimizing duplication
Partner with engineering, data analysis, data science and business teams to align data solutions with business needs. Mentor technical teams in data architecture best practices
Develop comprehensive architectural documentation and communicate data architecture principles to both technical and non-technical stakeholders
Conduct exploratory data analysis to elucidate deficiencies and opportunities with tangible evidence
Partner with other Distinguished Engineers across the enterprise to identify and foster investments in shared data services and platforms
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:
Hands on experience with AWS Cloud data technologies including RDS, DynamoDB, S3 and Glue ETL
Experience designing and implementing event based stream processing solutions using technologies such as Kafka, Kinesis, Spark and Flink
Ability to design and implement high availability, multi-region data replication for mission critical applications
Experience designing and implementing data management solutions that enable Data Quality, Reference Data Management, and Metadata Management.
A track record of designing and implementing end-to-end data pipelines supporting both production and analytic use cases
Comfortable coding with Python or Scala and proficient in SQL
In-depth understanding of AVRO, Parquet and DeltaLake data formats
Background using multiple data storage technologies including relational, document, key/value, graph and object stores
Demonstrated ability to partner with internal product and intent owners to help define requirements and outcomes for data-focused initiatives
Ability to decompose large problems and execute smaller, manageable bodies of work to demonstrate continuous architecture delivery
Understanding of machine learning and AI data infrastructure needs
Basic Qualifications:
Bachelor’s degree
At least 7 years of experience in Data Architecture and Data Engineering
At least 7 years of Data modeling and platform design
At least 2 years of experience in cloud computing (building applications in AWS )
Preferred Qualifications:
Bachelor's or Master's Degree in Computer Science or a related field
At least 2 years of experience with ontology standards for defining a domain
At least 2 years of experience using Python, SQL or Scala
At least 1 year of experience deploying machine learning models
Experience implementing knowledge graphs
Familiarity with Industry standards related to Data
Experience with data mesh, data lakehouse architectures and real-time data pipelines
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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