Senior Data Engineer (AI-Native) - Data Layer

About the role

people+ is recruiting on behalf of its client Proton.ai, which is building an AI operating system for wholesale distribution. It is looking for a Senior Data Engineer to join remotely from Europe, with meaningful daytime overlap with the Boston team. The role owns the Data Layer end-to-end, from ingestion and data modeling to the serving layer powering Proton.ai's products and AI systems.

Key responsibilities

• Build new data systems and pipelines from the ground up, owning architecture, implementation, deployment and production operations.
• Operate reliable ingestion and transformation pipelines using modern orchestration tools and cloud data warehouse technologies.
• Design and maintain data models using medallion architecture (raw, refined, curated layers).
• Build systems for data validation, reconciliation, lineage, backfills and incremental processing.
• Investigate and resolve data quality issues and help improve the architecture, tooling and scalability of the Data Layer.
• Use AI coding agents as part of daily development, reviewing and validating their output.
• Collaborate with backend, AI and product engineers, and occasionally with customers' IT teams, to define data requirements and contracts.

Required profile

• 7+ years of hands-on data engineering experience with a proven track record of production data pipelines, models and platforms.
• Proven experience building data systems from scratch, from architecture through to production.
• C1-level English and strong written and verbal communication skills.
• Ability to work in a fast-moving startup environment and to take data systems from idea to production.

Required skills

• Medallion architecture (raw, refined, curated layers)
• Programming and SQL, including designing efficient pipelines, schemas and queries
• Ingestion and ELT pipelines with orchestration tools
• Cloud data warehouse and a major cloud platform
• Handling files, APIs and streaming events; troubleshooting pipeline inefficiencies and query performance
• Managing partial loads, late or out-of-order data, schema changes, backfills and idempotency
• Guiding AI agents and reviewing their output

Big pluses: deep cloud data warehouse experience, streaming and event ingestion at scale, ERP or eCommerce integration, data systems supporting AI or ML products, and early-stage SaaS or startup experience. Pay is 90K - 105K depending on seniority and experience.