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Design and implement scalable cloud and on-premises data architectures using Snowflake and AWS Data Tools. Define data models, metadata, security, reference and master data standards; design data flows and reference architectures; optimize data delivery, automation and scalability; provide technical leadership to engineering teams and collaborate with stakeholders to align data strategy with business objectives.

Manage and grow enterprise airline accounts as the day-to-day commercial and relationship lead. Own client satisfaction, retention, revenue targets, pipeline, forecasting, renewals, and senior stakeholder engagement while partnering with delivery, solution architecture, and account leadership.

The Data Scientist develops data pipelines, machine learning models, and optimization models, integrating features into the product's technical stack and business processes.

The Data Engineer will design and build production-grade data pipelines and architectures for AI solutions, ensuring data quality and collaborating with cross-functional teams.

Lead definition and implementation of AI-first governance, guardrails, and controls for safe, auditable AI-assisted development across the SDLC. Partner with engineering to set standards for Copilot, AWS Q/Transform, Kiro, CodeScene ACE, repository controls, review evidence, and migration roadmaps while driving adoption and tracking AI risks and technical debt.

The Senior SRE/Platform Engineer will design and scale cloud platforms for AI-driven products, improving reliability, architecture, and infrastructure automation through Terraform and SRE principles.