Senior Data Engineer AI-Native - Data Layer - jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (AI-Native) — Data Layer based in United Kingdom.

This role offers the opportunity to build and scale the core data infrastructure behind an AI-powered platform transforming a major global industry. You will own the architecture, pipelines, and systems that ensure data is accurate, reliable, and ready to power intelligent products. The position combines deep technical ownership with innovation, requiring both strong engineering fundamentals and an AI-native approach to development. You will work on complex data challenges involving multiple sources, large-scale processing, and modern cloud technologies. Your contributions will directly influence how businesses leverage data and AI to improve operational efficiency and decision-making. This is an opportunity for an experienced engineer who thrives in a fast-moving environment and enjoys building foundational systems from the ground up.

Accountabilities:

The Senior Data Engineer will own the development and evolution of the Data Layer, ensuring that all data systems are scalable, trustworthy, and optimized for AI-driven applications. This role requires end-to-end ownership, strong technical judgment, and the ability to design solutions that support both current products and future growth.

• Own the Data Layer architecture, including ingestion pipelines, medallion-style data models, and serving layers.
• Design, build, and maintain reliable ingestion and transformation pipelines across various data sources.
• Integrate and reconcile complex real-world data from file-based systems, streaming events, and APIs.
• Develop data models across raw, refined, and curated layers to ensure data quality and accessibility.
• Build systems that guarantee data reliability through validation, reconciliation, lineage tracking, backfills, and incremental processing.
• Improve the scalability, performance, and tooling of the data platform as requirements evolve.
• Leverage AI-powered development tools to accelerate engineering workflows while maintaining high standards for code quality and reliability.
• Define and maintain data contracts in collaboration with backend, AI, product, and customer-facing teams.
• Troubleshoot complex data issues and ensure downstream systems and AI applications receive accurate information.
• Take ownership of projects from concept through production, making thoughtful decisions on architecture and implementation.

Requirements: