Senior Data Engineer (AI-Native) — Data Layer

Role overview Own the data foundation behind a suite of products and AI features, from incoming source data through transformation and serving. This is a hands-on senior role combining data architecture, production pipeline ownership, and active use of AI coding agents, with responsibility for making the resulting data reliable for downstream teams.

Responsibilities - Design and operate ingestion from files, events, and APIs, along with raw, refined, and curated data layers and the serving layer. - Build and maintain reliable ingestion and transformation workflows using orchestration tools and a cloud data warehouse. - Reconcile inconsistent source data and establish validation, lineage, backfill, incremental-load, and idempotency practices. - Improve the data platform’s architecture, tooling, scale, and source coverage. - Use coding agents to plan and implement work, review their output, and ensure production quality. - Partner with backend, AI, product, and sometimes customer IT teams to define dependable data contracts.

Requirements - Seven or more years of hands-on data engineering, with production ownership of pipelines and models serving real users at scale. - Strong programming and SQL skills, including data modeling for analytical and transactional use cases. - Experience building orchestrated ingestion or ELT pipelines from messy upstream sources, using a cloud warehouse and major cloud platform. - Practical experience with file, event or streaming, and API sources. - Ability to diagnose query and pipeline performance issues and trace data correctness problems to their cause. - Understanding of partial loads, late or out-of-order data, schema drift, idempotency, and backfills. - Daily experience using agentic coding tools to deliver work, with the judgment to verify results and explain technical decisions. - Clear communication and English proficiency at C1 or above.

Nice to have - Experience with modern transformation tools, streaming at scale, or medallion and lakehouse architectures. - Work integrating enterprise ERP or ecommerce systems and reconciling transactional data. - Experience supporting AI or machine learning products through serving layers, retrieval, or model data contracts. - Background at an early-stage software company.

Benefits and work setup - Remote within Europe, with meaningful daytime overlap with a team based in Boston.