AI Data Engineer

Join Quantifind as an AI Data Engineer on the AI Systems team. You will drive data prototyping, experimental ETL pipelines, and data discovery. Your responsibilities will include building and managing reliable ETL pipelines, performing data quality assurance, and managing data compliance and documentation. You should have experience with large data pipelines, high-performance computing, and AWS cloud management.

• Conduire la prototypage de données et les pipelines ETL expérimentaux, en mettant l'accent sur la vitesse et la fiabilité.
• Gérer l'acquisition de données, l'ingestion de données commerciales et la découverte de données, y compris l'intelligence open-source.
• Construire et gérer des pipelines ETL fiables, en se concentrant sur l'indexation des bases de données, l'optimisation des performances et l'équilibrage de charge.
• You bring a data architecture mindset, and are focused on ontologies, frameworks, documentation, and unifying value across heterogeneous sources into knowledge graphs
• You're also an engineer who codes with AI as a first-class tool, not an add-on
• You're comfortable managing complexity across both structured and unstructured pipelines, and you're genuinely curious about data: its provenance, its quality, and its ultimate value to customers
• You move fast, iterate with stakeholders, and care about shipping things that work
• You are familiar with investigative products built on open-source intelligence
• You've built and managed large-scale ingestion pipelines from discovery through to performant products in high-stakes systems
• You are an experienced data engineer with a modern AI tooling perspective
• You pair traditional technical training with a forward-leaning approach to agentic coding, rapid prototyping, and multi-agent workflows
• You have a responsible mindset and are familiar with the legal and compliance limits on data use
• Experience with large data pipelines, high-performance computing, and Spark/PySpark
• Ability to provide references and meet in person
• Self-driven, mission-driven, curious, and constructive — a startup mindset with strong communication skills
• Core stack: Python. Helpful: Spark/PySpark, Scala, and other large-scale data tooling
• Solid AWS cloud management experience
• 4+ years of professional experience, including graduate or Ph.D. work if relevant
• Technical education
• Knowledge-graph and ontology frameworks (e.g., Neo4j)
• Forward-leaning in AI coding, with traditional technical training as a foundation
• Database management experience: PostgreSQL, RDS
• Hands-on with AI coding tools and agentic workflows (Claude Code, GPT/Codex, Cursor, Windsurf), including multi-agent approaches for testing and validation
• US Citizen