Senior AWS Data Architect

The AWS Data Architect is responsible for the overall strategy, design, and implementation of the company’s data infrastructure on Amazon Web Services (AWS). This role requires a strategic mindset focused on translating business outcomes into technical architecture, enabling automation, and defining data integration patterns for various use cases. The architect will lead the transition from a current state to a target state data ecosystem, proposing and executing viable options based on both short- and long-term business needs. Additionally, the role will involve incorporating advanced AI architecture, including agentic AI, vector databases, Model Context Protocol (MCP), and Retrieval-Augmented Generation (RAG). Team Culture

Collaboration is the key to success with this fast-paced team. While each person holds an area of expertise, we all join in to support the customer. Through weekly meetings, group huddles, and 1 on 1 peer training, everyone is given the opportunity to brainstorm, ask questions, and find solutions. We support and lift one another up to achieve more together. How You’ll Spend Your Time

• You will document current and target state data architectures, including interim states and migration roadmaps using AWS and other tools.
• You will present strategic execution options that weigh business impact, cost, risk, and timelines.
• You will align data initiatives with business goals to deliver measurable outcomes like improved customer experience and faster time-to-market.
• You will create and maintain robust reference architectures for batch, near-real-time, and real-time data flows from diverse types of sources.
• You will architect and implement scalable, low-latency data pipelines using Apache Kafka.
• You will integrate advanced AI architectures such as vector databases, MCP, and RAG to enhance data processing and retrieval.
• You will promote automation, CI/CD practices, and establish patterns, reusable templates, enabling rapid, consistent development for engineering teams.
• You will drive data governance and data quality by implementing best practices throughout the data lifecycle.
• You will provide leadership and technical guidance while mentoring teams and promoting innovation.

The required level of knowledge is normally acquired through completion of a Bachelor’s Degree in information systems, data analytics or a related field and 15+ years’ experience in a data discipline such as developing and implementing data framework, reference models, or data modeling (operational and analytical). Certification in TOGAF (or similar framework required)