Analytics Engineer

il y a 1 semaine


Clichy, France L'Oréal Temps plein

Join to apply for the Data Analytics Tech Lead role at L'Oréal Mission Your Mission: Architecting Data-Driven Financial Insights Key Challenges Harmonizing analytics practices, optimizing data and tool governance, enabling semantic modeling at scale, and continuously scouting for the next generation of analytics capabilities and technologies. Portfolio Iclosing: An augmented analytics webapp tool integrated with Looker, delivering reactive insights for controlling and accounting teams. Global analytical tools: Strategic cockpits, trackers, dashboards and semantic models developed on Looker and PowerBI. Conversational GenAI Assistant: Pioneering the use of generative AI for finance. What You'll Be Doing A Blend of Vision & Execution Main Responsibilities Strategic Product & Platform Ownership: Define the future, shape the product vision and priorities for our analytics platforms within the finance domain. Business translation: Expertly gather requirements from finance stakeholders, translating complex business needs into sustainable, impactful analytical solutions (visualizations, reports, dashboards, custom interfaces, web applications). Scope & Prioritize: Lead the scoping and prioritization of projects related to Analytics architecture, including semantic modeling, access governance, and monitoring. Architecture, Development & Delivery Excellence: Design, develop, and evolve state-of-the-art analytical solutions within the Finance domain. Technical Leadership: Define the target architecture of the Finance Analytics stack in relation to Group Data Strategy, ensuring its scalability, performance, security, and maintainability. Best Practices Champion: Own and enforce development best practices and norms, ensuring high-quality outputs and guiding external consultants. Empower & Mentor: Guide and teach Data Analytics developers and functional teams on best practices and optimal solutions using our technological stack. Drive Implementation: Oversee the technical implementation of solutions in collaboration with data/IT teams. Continuous Improvement: Propose and implement innovative solutions, enhance user experience, consolidate documentation, analyze recurring issues, design automated tests, and transform application support from reactive to proactive. Semantic Layering: Structure semantic layers tailored for Self-Service BI use cases and ensure wide adoption of tools and solutions. Innovation & Technology Watch: Continuously monitor BI and analytics market trends, identifying technologies with high potential for L'Oréal, particularly within the finance context. Strategic Contribution: Proactively contribute to the global technical roadmap for the finance domain, focusing on data & analytics and progressively integrating AI subjects. Pioneer & Test: Test and recommend relevant emerging solutions (e.g., Text2Analytics, AI-augmented BI). Technical Mastery & Experience Proven experience (7+ years) delivering large-scale data analytics applications end-to-end, ideally within the finance domain. Solid experience in BI solution development with both Google (Looker, BigQuery) and Microsoft (Power BI, Fabric) ecosystems. In-depth understanding of cloud database systems, data modeling, and semantic concepts. Advanced knowledge of SQL queries and potentially MDX, DAX, and LookML. Proven experience overseeing front-end development for analytical interfaces is highly preferred. Experience in analytics solution architecture/lead/design. Experience in at least one relevant programming language (e.g., Python, R) is highly preferred. Experience with ETL development is a strong plus. Functional & Project Acumen Demonstrated experience working seamlessly with business users to gather requirements, manage scope, and drive adoption. Strong experience with Finance domain projects and intricate Finance data. Proven motivation to lead and mentor technical teams. Experience with Agile development frameworks. Strong time management and organizational skills, with the ability to manage multiple timelines and priorities. Mindset & Soft Skills A results-oriented mindset with a proactive, innovative, and problem-solving spirit. Strong team player with excellent communication skills (oral and written). Rigorous, detail-oriented, and highly curious with a strong capability for continuous learning and adapting to new technologies. Education Master’s Degree in Computer Science, Engineering, or a relevant technical field, or equivalent work experience. Fluent English (oral and written) is essential, French. #J-18808-Ljbffr


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