Enterprise Data Architect- AWS

Duration:12+ MonthsLooking for an individual who has been in the data engineering space and has a flair for architecture who understands the different AWS services that can be used to design a solution that conforms with the well architected pillars. Knowledge of Snowflake is a good to have. Knowledge of AI/ML – who has knowledge on the different Gen AI capabilities and tools to design and build safe, secure and responsible AI solutions. Knowledge of Agentic frameworks and MCP patterns.The Associate Architect will work with senior architects and delivery partners. You will ensure that all relevant project teams follow a common set of principles and patterns that utilize a standard set of technology frameworks and libraries while applying architecture standard methodologies that help increase execution velocity.This associate will be responsible to research and conduct POCs to ensure solutions are built in alignment with platform principles and standards and drive the architecture for key cross team/cross product development projects (via architecture/design documents and developing code key modules).Primary Skills:Bachelor’s Degree in a related field (Computer Science, AI/ML).8 to 10 years of IT and business/industry development experience2 to 4 years of AI/ML knowledge (not a data scientist but knowledge on AI/ML capabilities, patterns and integrations)Knowledge of data standards (security, ingestion, warehousing, storage)Validated knowledge of successful design, architecture and development using AWS Cloud technologies.Experience with AWS product categories like Analytics, Application Integration, Compute, Database, Serverless.Experience with SnowflakeExperience with AI/MLCollaborate with Agile teams to recommend the right architectures with high quality and software standard methodologiesStrong communication skills.Nice to have:Experience with One or more data Integration Technologies (Matillion, Pentaho, Datastage, etc.).API’s, Apigee, Developer Portals. Expertise in JSON, RESTful services, and similar related techExpertise in R, Python and predictive analytics.Containers: Docker, Kubernetes, OpenShift, Ansible, Nexus, Software defined networking.DevOps/DevSecOps: Chef, Puppet, Jenkins, Packer, Git, GitHubThe Work Itself:Developing data integration architectures and define architecture standards & guidelines (architecture and design patterns)Defines deployment topology by working with peers across the technology organization.Optimizes use of Ally’s Platform and technologies.Work with Business and delivery partners to understand future requirements and implications for architectureIdentify architecture solution alternatives, driving business requirements, and availability of new technologiesIdentify new technologies and tools to support architecture(s) and determine architectural roadmapsEncourage early adoption of tools and architecture across the organizationReview solutions and projects to ensure they are consistent with standard methodologies in data and analytics