Product Manager

Join our team as a Data Product Manager, where you will manage the daily lifecycle of our core data assets. You will treat data as a first-class product, executing the delivery roadmap from initial data ingestion and modeling through to engineering and deployment. This role requires strong technical execution and product management discipline, with a focus on engineering and optimizing underlying data structures, APIs, and algorithmic logic. You will also monitor product performance, operationalize insights, and ensure decision consistency across diverse segments, regions, and customer footprints.

• Gérer le cycle de vie quotidien des actifs de données, de l'ingestion initiale des données à l'ingénierie et au déploiement.
• Travailler en étroite collaboration avec les propriétaires de processus métier pour intégrer des modèles prédictifs, des moteurs de règles et des informations basées sur les données directement dans les flux de travail opérationnels.
• Suivre la santé des données, les métriques du produit et la fiabilité des pipelines, et affiner continuellement les modèles pour résoudre les dérives.
• Product Delivery: Experience managing a product backlog, writing technical user stories, participating in sprint cycles, and prioritizing engineering tasks
• Data Experience: 5+ years of experience working directly with data-centric products, data platforms, data APIs, or analytics infrastructure (e.g., as a Data Product Manager, Technical Product Manager, Data Analyst, or Data Engineer)
• Requirement Mapping: Ability to translate defined business goals into structured data requirements, identifying the inputs and logic parameters needed
• Advanced SQL Mastery: Expert-level SQL skills to write highly optimized, complex analytical queries. Proficiency with window functions, Common Table Expressions (CTEs), nested fields, and performance tuning for massive datasets
• Google BigQuery Expertise: Hands-on experience navigating the BigQuery architecture. Competency using BigQuery features like partitioned/clustered tables, materialized views, and BigQuery ML for rapid model deployment
• Google Cloud Platform (GCP) Ecosystem: Solid understanding of core GCP data infrastructure tools (e.g., Cloud Storage, Dataflow, Dataproc, Pub/Sub, Vertex AI) used to orchestrate, store, and stream data across enterprise applications
• Rules Engines: Familiarity with recommendation logic architectures and dynamic optimization rules engines
• Manages stakeholder expectations within and/or across functions
• Scripting Capabilities: Fundamental proficiency in Python or equivalent scripting languages to manipulate data, connect to cloud APIs, and test functional logic prototypes
• API Fundamentals: Good understanding of how APIs and microservices are used to stream data product outputs from cloud environments into target business systems
• Team Liaison: Ability to communicate clearly and coordinate effectively between technical engineering teams (Data Engineers, Data Scientists) and commercial business users
• Bachelor's degree preferred
• 5+ years experience preferred
• Analytical & Algorithmic Domain Knowledge
• Modern Data Engineering: Practical understanding of basic ETL/ELT pipelines, data transformations (e.g., using dbt within BigQuery), and data warehousing concepts
• Predictive & Scoring Logic: Foundational understanding of predictive modeling, scoring algorithms, look-alike logic, and data segmentation frameworks
• Identifies and proactively includes correct stakeholders and communications effectively
• Problem Solver: Analytical mindset focused on troubleshooting data flow issues and translating technical complexities into clear project status updates