Senior Data Engineer (AI-Native, Data Layer)

Join Proton as a Senior Data Engineer and take ownership of our Data Layer, the foundation for all our products and AI. You'll be responsible for end-to-end architecture, ingestion from various systems, and ensuring data correctness. This role requires meaningful daytime overlap with our Boston team and offers a range of benefits, including company stock options, flexible scheduling, unlimited PTO, and more.

• Posséder et développer la couche de données, y compris l'ingestion, la transformation et la modélisation des données.
• Construire et exploiter les pipelines d'ingestion et de transformation qui alimentent la couche de données, en utilisant un cadre d'orchestration moderne.
• Travailler en étroite collaboration avec les équipes backend, IA et produit pour définir les contrats de données sur lesquels elles s'appuient.
• Strong programming and SQL skills. You build efficient pipelines, schemas, and queries, and can model data for both transactional and analytical access patterns
• Daily, hands-on use of agentic dev tools (Claude Code, Cursor agent mode, Codex, or equivalent) to ship real work. You can talk concretely about how you structure prompts, manage context, parallelize agents, and verify their output
• English at C1 or above
• Hands-on orchestration experience, building reliable ingestion/ELT pipelines against messy upstream sources
• Solid grasp of data-consistency failure modes — partial loads, late or out-of-order data, idempotency, backfills, schema drift
• Startup mindset and strong communication — pragmatic, fast, biased to ship, and able to explain data decisions to engineers, PMs, and customers in writing
• Experience with a cloud data warehouse and a major cloud platform
• Ownership and judgment. You take data systems from idea to production and exercise good taste on what to build and what to cut
• 7+ years hands-on as a data engineer with real, demonstrable production ownership — pipelines and data models serving real users at scale
• Experience ingesting from multiple source types: file-based, event/streaming, and API-based
• Strong fundamentals. You understand what your code and your queries are doing and why. You can read a query plan, reason about a slow or expensive pipeline, and debug a data-correctness bug to its root
• Deep cloud data warehouse experience and modern transformation tooling
• Streaming / event ingestion at scale
• Medallion or lakehouse architecture experience on large, multi-source data
• Experience integrating enterprise sources such as ERP (Epicor Eclipse, Prophet 21) or ecommerce systems, and reconciling messy transactional data
• Building data systems that feed AI/ML or agentic products — serving/feature layers, retrieval, or data contracts for model inputs
• Prior experience at an early-stage SaaS startup