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Information Architect

Req #: 180003549
Location: Wilmington, DE, US
Job Category: Technology
Job Description:
Chase Consumer and Community Banking (CCB) serves more than 65 million consumers and 4 million small businesses with a broad range of financial services, including personal banking, small business lending, mortgages, credit cards, payments, auto finance and investment advice.  
 
CCB is driving a large organizational transformation, including alignment to products and services, customer-centric outside-in engineering and autonomous applications that greatly increase our speed and agility.  Underpinning this transformation will be large growth in distributed data, events and ‘intelligence’ that will be the foundation for improved customer experience.  Managing and governing the growth is essential to ensuring compliance to policies, standards and patterns and will require additional taxonomies, developer accountabilities and increasingly automated governance that is engineered into the software delivery process. 
In this role, the CCB Information Architect will play in integral role in:
  1. Defining support model and guidance for new data management technology and platforms, especially related to autonomous applications and the opinionated stack;
  2. Defining and deliver frameworks and techniques to accelerate data definition for developers, available in tools they use, to drive velocity around consistency and compliance;
  3. Driving progressive/modern standards and specifications for developers to ‘annotate” in code that provide the basis for automating governance to standards as well as detecting sprawl though machine learning; and
  4. Driving adoption of Firm Data Management standards and artifacts that can be evidenced for compliance.  Emphasis will be on doing this at scale, leveraging modern techniques and developer accountabilities to ensure software and data is understood from the start.
The ideal candidate should be progressive in strategy, standards and enablement across information architecture and data management to balance offensive (monetization, recommendations and experience) and defensive (regulatory/compliance) data management practices.   
 
Key Responsibilities:
Modern Data Practices Enablement:
  • Autonomous Applications standards and governance
    • Prioritize and define standards around naming and metadata to drive consistency and transparency while establishing the baseline for automated governance
    • Participate in definition of key business taxonomies around products and services to organize, guide and govern the business transformation and domain driven design 
    • Define a position on the metadata strategy, standards and mandates for autonomous applications in context of the bigger CCB metadata strategy (MDR).  This should include autonomous applications & private data, events, APIs and information flows/exchanges with 3rd parties. 
    • Guidance on appropriate use of data management technologies given the opinioned stack (Cassandra)
  • Data Definition and Compliance Accelerators for our software engineering community
  • Work with Engineering and Architecture to integrate data definition into tools developers use to increase definition and compliance velocity.  This may include identifying data objects/subject areas of data, converting those data dictionaries into formats (Swagger/YAML) that can be imported and used within the API developer portal or Java IDE.
  • Identifying techniques to inspect/infer data elements/definitions with fast feedback within the tool chain ‘design’ as well as transparent understanding of approved SORs for data domains/elements
  • Collaborate with Firm CIA to integrated compliance scanning into the tool chain
  • Automate Data Discovery Intelligence
  • Framework and approach to improve data domains and semantic discovery via machine learning, at scale, to improve understanding of legacy footprint and transparency going forward. 
  • Position on tools to improve usage, depth of data and utilization to improve cost and risk posture. 
  • Automate identification of Firm Strategic Reference Data to insure compliant design and sourcing
  • Automate Governance
  • Participate in the definition, approach and foundations to increasingly automate portfolio governance in an autonomous application and event driven environment.  
  • This should include developer accountabilities and self-describing code that provides a live sense of end to end business processes that can be subsequently mined via machine learning to identify sprawl or anomalies
  • Determine a scale approach to ensure each database change has approved logical / physical metadata, including sourcing, protection, and retention metadata. (data change as code)
  • Participate in retrospectives and continuous improve of Product Architecture Solution Intent as well as CCB microservice and API governance
Firm and CCB Data Management Alignment:
  • Align CCB and Firm data modeling standards and implement in data model templates, governance and metadata publishing processes. Collaborate on processes and tools to facilitate migration.
  • Evaluate and align CCB and Firm processes and taxonomies for Authoritative Source Inventory, including maintenance process to support new requirements.
  • Evaluate Firm Data Management tools against CCB requirements and recommend how to use from a target state perspective to increase compliance and developer velocity.
Firm Critical Business Initiatives:
  • Support prioritized Firm Critical Business Initiatives.
Metadata Coverage and Health:
  • Define and implement scorecards (control reports) to assess metadata quality and completeness for data models, data registration, and other capture mechanism.
  • Define techniques to inspect metadata sources for anomalies or sprawl.
  • A minimum of 10 years of IT experience, with 8+ years in Information Architecture / Data Modeling in Transactional, Data Warehousing, Business Intelligence or Master & Reference Data Management
  • Bachelor's degree in Science, Business or Arts is required; Master’s degree is Computer Science is preferred.
  • Strong leadership, partnership and communication skills, tailored to the audience’s level of knowledge.
  • Strong understanding of the financial services industry vertical, focused on Retail Banking
  • Expert in conceptual, logical and physical data modeling using tools such as Erwin
  • Experience with Data Management and Data Governance
  • Experience with enterprise metadata, reference data and data quality, including analysis and faming facts
  • Excellent influencing and consultative skills, including business and technology interactions                                                                                                                                  Additional Desired Qualifications (candidates not expected to have all of these)
  • Experience in performing ‘data forensics’ to discover and infer data managed and to strategize on data rationalization opportunities, given the facts,  across the business data and storage infrastructure
  • Experience in industry research and leveraging industry data models, standards, patterns and open source products, as appropriate, to increase consistency in data definition and developer velocity
  • Logical and Physical database modeling skills (i.e., Oracle, Teradata, and DB2) and understanding of dimensional modeling
  • Experience in highly distributed databases, event streaming – private and public cloud
  • Experience in data profiling and interpreting results  to support data modeling tuning and data quality
  • Experience with metadata repository product(s), including future looking and future positioning
  • Understanding or experience with data mining and/or statistical modeling
  • Exposure to Agile and data management practices
  • Understanding of emerging data persistence and processing paradigms, including Hadoop, Cassandra, and other NoSQL databases
  • Experience implementing data pipelines in big data technologies such as Hadoop, Kafka, Spark, Redshift
  • Shows passion for hands-on work in the metadata and data engineering space with an eye on ways to  increasingly automated governance practices and a live sense of the data
 
 
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