Product Data Solutions Architect

[email protected]
Reply to: [email protected]
Job Title: Product Data Solutions Architect (5 roles) Location: Located in one of the following states (CT, DC, DE, GA, IL, KY, MA, MD, ME, NC, NH, NJ, NY, PA, RI, SC, TN, VA, VT, WI, WV)
Top 3 requirements: Kafka experience Team/technical lead experience. Answer technical questions help others, strategize Mongo DB/No SQL Agile exposure Cloud Solutions Architect Certificate or something similar Data Visualization tools like PowerBI, Tableau etc MS Azure is a plus+ Day to Day Responsibilities/project specifics: Lead the analysis, design, and implementation of a comprehensive business data product, with results that can be seamlessly expanded to address other business domains Embed with feature teams during early design phases to consult on data, systems architecture, and API design decisions, ensuring consistent system and data models Plan, participate, design, review, and structure data design review sessions. Take accountability for ensuring all key design and compliance decisions are reviewed and approved before implementation following all data architecture guidelines set Ensuring adherence to proper data design and security for new cloud data platform and data products and new enhancement features Responsible for data model and schema documentation into governance systems Responsible for canonical models for APIs, Event Streams, and Data as a Service Participate in defining standards for data quality and creating data test and validation plans Empower Data Product Squads to follow better design paths with automated quality engineering and automation Represent the data products in the creation of enterprise data models and corporate data standards Stay up to date on relevant technologies, plug into user groups, and understand trends and opportunities to ensure we are using the best possible data-centric techniques and tools Ability to work in a cross functional team and collaborate with multiple Data Product Squads Collaborate with Data Science teams to power the machine learning platform to support modeling and serving Collaborate with Solution Architects from other products, Enterprise Architects to design better data products that fit to the needs of the organization