Sr. AWS Data Architect

Signet Jewelers is the world's largest retailer of diamond jewelry, operating more than 2,800 stores worldwide under the iconic brands:
Kay Jewelers, Zales, Jared, H.Samuel, Ernest Jones, Peoples, Banter by Piercing Pagoda, Rocksbox,  and Diamonds Direct.

We are a people-first company and this core value is at the heart of everything we do, from empowering our valued team members, to collaborating with our customers, to fostering the communities in which we live and serve. People – and the love their actions inspire – are what drive us. We’re not only proud of the love we inspire outside our walls, we’re especially proud of the diversity, inclusion and equity we’re inspiring inside.

There are dynamic career paths awaiting you – rewarding opportunities to impact the lives of others and inspire love. Join us! We are seeking an experienced Sr. AWS Data Architect to provide architectural leadership for the design, modernization, governance and evolution of enterprise data platforms, with a strong focus on establishing a trusted, scalable, secure, governed and reusable data foundation that enables enterprise analytics, BI, machine learning, generative AI and agentic AI.

This role combines enterprise architecture ownership with hands on technical expertise to deliver scalable, secure, resilient and cost effective data solutions aligned with business objectives and the enterprise data strategy. The ideal candidate will define the future state data architecture, reference architectures, technology standards, design patterns, and strategic roadmaps while providing architectural oversight across analytical, operational, API based, event driven, and real time data workloads.

• 1. Enterprise Data Architecture and Strategy Define and own enterprise data architecture strategies, future state architectures, architectural principles, technology standards and modernization roadmaps aligned with business and enterprise objectives. Lead architecture assessments, technical feasibility studies, design reviews and Architectural Review Board activities, providing recommendations on technology selection, solution design, architectural risks and exceptions. Evaluate emerging technologies and architectural patterns, ensuring tactical implementation decisions support long term enterprise goals, and communicate technical recommendations and trade-offs to business and technology leadership.
• 2. AI Ready Data Foundation & Architecture Define the architecture and roadmap for an AI ready enterprise data foundation that supports analytics, ML, GenAI and agentic AI solutions, enabling secure and scalable consumption of structured, semi-structured and unstructured data Define reusable architecture patterns for RAG, embeddings, vector search, enterprise knowledge integration and governed model access. Partner with Data Governance, Security, Engineering and AI teams to establish responsible AI data controls and standards.
  
  Architect scalable, secure, highly available, resilient, and cost-effective data platforms using AWS native services, including Amazon S3, Redshift, RDS, AWS Glue, Lambda, Kinesis, Event Bridge, API Gateway, SQS, SNS, IAM, and Cloud Watch. Design end-to-end architectures for data ingestion, integration, storage, processing, transformation and consumption across batch, streaming, event driven, API based, analytical and operational workloads. Establish architectural best practices for performance optimization, disaster recovery, cloud security, observability and cost management Define secure by design architecture standards covering IAM, least privilege access, encryption, network connectivity, data protection and compliance requirements.
  
  Establish standards for monitoring, logging,…