Provides positive user experience by determining information structure for Web sites and Web applications.
Identifies user requirements by researching and analyzing user needs, preferences, objectives, and working methods; studying how users consume content, including data categorization and labeling; meeting with focus groups.
1. Plans information architecture by studying the site concept, strategy, and target audience; envisioning architectural scheme, information structure and features, functionality, and user-interface design; creating user scenarios; preparing data models; designing information structure, work-and dataflow, and navigation; evaluating information representation; conducting creative meetings.
2. Organizes information by translating user behavior into media structure and elements; crafting interactive experiences; producing workflow diagrams, user scenarios, flowcharts, and storyboards; preparing interaction specifications, navigation rules, organization of information, and site maps; coordinating with business, technology, visual, structural, editorial, cognitive, and brand strategists.
3. Implements information architecture by preparing paper and interactive prototypes and mockups including page layout and navigational elements; coordinating with Web Producer and Production Developer to integrate site concept, visual design, writing, interface, and navigational structure; documenting structure and processes.
4. Validates information delivery by developing and completing usability test plans; evaluating traffic patterns; studying user feedback; coordinating with Usability Specialists.
5. Enhances organization reputation by accepting ownership for accomplishing new and different requests; exploring opportunities to add value to job accomplishments.
Skills and Qualifications:
• Has a minimum of 10 years of experience in data warehousing and big data architecture solutions.
• Lead the design of architectural roadmaps, database, data access and data technology architectures
• Provide expertise on the overall data eco-system’s engineering best practices, standards, architectural approaches and complex technical resolutions
• Knowledge and hands-on expertise in the following technologies: Cloud Data Lakes, RDBMS, NoSQL, Big Data Hadoop technologies, distributed technologies, ETL tools, data modeling for transactional as well as reporting focuses.
• Experience in technologies like: Spark, Apache Kafka, Kenesis, BI and Datawarehousing, Hive, Presto, Flume, Storm
• Team player, strong influence, and relationship management skills