Chase is the U.S. consumer and commercial banking business of JPMorgan Chase & Co. (NYSE: JPM), a leading global financial services firm with assets of $2.3 trillion and operations in more than 60 countries We serve more than 50 million consumers and small businesses through more than 5,600 bank branches, 18,700 ATMs, credit cards, mortgage offices and online and mobile banking as well as through relationships with auto dealerships.
Within Chase, Consumer Banking provides great products and an outstanding customer experience at over 5,600 branches and 18,700 ATMs in 23 states, as well as online and over the phone.
As a Chase employee, you’ll be part of a company that makes a real difference every day for our customers, our communities and ourselves. With a focus on customer service, you’ll put others first, do what’s right and create solutions that make lives better. We invite you to build your career on our strong foundation and help shape what’s next – for you and for us.
This position is responsible for the technical and process solutions to strategic projects affecting CCB Operations. This IT leader is responsible for ensuring the delivered solutions meet the critical business needs while complying with and advancing the IT strategic direction for CCB. This leader is also responsible for maintaining and building reference material which describes the existing technology assets and their alignment to CCB functions and capabilities.
The Solution Architect works directly with business and IT leaders across CCB lines of business to understand the business need, the current architecture, and to evaluate solution options and impacts. The CCB Solution Architect works with IT personnel across disciplines (data, infrastructure, development, production support) and with LOB business operations to define and deliver the recommended solutions.
Key responsibilities include:
Overall: Strong and effective communication skills. Able to roll-up presentations to an executive readout level. Able to present to architecture peers and boards and cross-domain technical audiences. Strong cross-team collaboration and leadership skills. Understanding of Cloud Economics and architecture decisions based on CapEx and OpEx impacts on operational Run Rates and overall TCO. Think Big but able to Execute on Vision (Technical acumen).
1. Contact Center
a. Good knowledge of vendor applications and solutions synthesized via their associated API frameworks : Genesys, Nuance, Verint, in particular for omni-channel management, context and session interaction management , voice biometric, workforce optimization, real time voice analytics, virtual agents, bots, server and client side application integration.
b. Understanding of Media Management (Protocol interworking: SIP-SIP, SIP-H.323, H.323-SIP, Media interworking Transcoding, Media Services: Replicate media for call recording, clean up media (echo cancellation) and inject media (MOH), SIPREC – with failover of call recording servers, Video: Codec H264/5 with VP8, SIP DTMF inband(signal)/out of band(media), IPv4/IPv6, Session and Call Admission Control).
c. Understanding WebRTC (ICE/STUN, Transcoding (Opus, VP8/9, H.264/5, G.711, G.729), Session controls (network, device handoffs, rehydration), Adaptive QoS controls on Internet),
a. Understanding of Cloud Services ( IaaS, PaaS and SaaS) and Deployment Models (Public, Private, Hybrid, On-premise)
b. Understanding of AWS PaaS microservice creation and management ecosystem
c. Understanding of Digital Architectures (Application development and container management (Spring, Scala, Docker), principles of fault tolerant microservices construction and management
d. Working experience with Cloud development stacks:
i. OpenStack, CloudStack, VCloud, EC2 for Hybrid Configurations and Managed Cloud Considerations
e. Understanding right implementations and tradeoffs of open source message brokers such as Apache ActiveMQ, Kafka, JMS
f. Understanding of elastic non-structural databases (MongoDB, Cassandra) and data modeling tools (see Data Modeling section).
g. Web Services, Rest API and RAML API creation standards
h. Understanding exporting on-premise contact center software layers in a cloud PaaS (i.e. AWS – see Contact Center section)
i. Encryption of data and indexes in Cloud with private KMS (Key Management System) and overall Security Considerations
3. Data Modeling
a. Understanding of semantic/logical schema definitions to support Presentational Dash-Boards, and Actionable Operational and Provisioning Cockpits drawn from disparate Contact Center sources ( application level API, real time events CTI, real time Context Stores)
b. Understanding of semantic and physical modeling against disparate data stores (Structured Databases, Key Value Stores, Column Family Stores, Big Data Stores)
c. Knowledge of data modeling tools (Dimensional Fact Modeling, Erwin, ER/Studio, Oracle Data modeling tools) – in various logical formats ( tabular, nested, graph
d. Good understanding of Lamda Architecture and Polyglot Persistence
e. Understanding of Modeling for Real Time Analytics ( Hadoop HDFS and Cloudera MapReduce and Apache Spark and Storm methods data processing methods) – See other sections (Cloud, Contact Center)
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