Senior Data Infrastructure Engineer

Join Storyful, a leading social media intelligence agency, as a Senior Data Infrastructure Engineer. In this hands-on role, you will design and build the technical foundations for scalable and reliable data and AI products. You will work closely with machine learning engineers, software engineers, product managers, and leadership to turn raw structured and unstructured data into trustworthy product capabilities. Your responsibilities will include building scalable batch and streaming pipelines, owning the ingestion and processing architecture, and creating the platform foundations for AI products. You will also define data contracts, improve pipeline reliability, and contribute hands-on code while mentoring other engineers.

• Conception et construction des couches d'ingestion, de traitement, de stockage et de service qui alimentent les futurs produits d'IA et de données.
• Collaboration avec les ingénieurs en apprentissage automatique, les ingénieurs logiciels, les chefs de produit et la direction pour transformer les données brutes en capacités de produit fiables.
• Responsabilité de l'architecture d'ingestion et de traitement pour les documents, le texte, les métadonnées et d'autres sources de contenu.
• This is a senior individual contributor role for someone who is strongest in data engineering but comfortable operating across AI infrastructure, retrieval systems, cloud architecture, and product delivery
• Strong experience in data engineering or platform engineering in production environments
• Excellent Python skills and solid SQL fundamentals
• Strong cloud engineering experience in AWS, GCP, or Azure, with clear transferability across platforms
• Experience with infrastructure as code and modern deployment practices
• Ability to work cross-functionally and act as a technical leader without losing hands-on depth
• Experience building reliable ingestion and transformation pipelines at scale
• Strong understanding of data modeling across structured and unstructured datasets
• Experience with distributed systems, event-driven patterns, and data-intensive applications
• Familiarity with search, vector, or retrieval systems used in AI-backed products
• Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, Temporal, or equivalent
• Search indexing, retrieval, semantic chunking, or RAG pipeline design
• Document processing pipelines for PDF, HTML, text, or media-rich content
• Graph databases, knowledge graphs, or entity/relationship-heavy systems
• Data quality, lineage, observability, and governance in regulated or high-trust environments
• Experience supporting agentic products with strong guardrails and human-in-the-loop controls
• Experience in media, intelligence, risk, trust, or other information-dense domains