Data Analytics Manager

About the role

Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees. Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world's leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations. The Data Analytics Team You will join our Data Analytics Chapter, a team of 60 professionals with expertise across dashboarding, analytics engineering, marketing measurement, and low-code data science. We are one of three technical teams at Artefact (alongside Software Engineering and Data Science), forming a tech community of 160 people. Despite working on different client engagements, we maintain a strong culture of knowledge sharing through dedicated communities of practice. We are growing fast, with the ambition to double our team size over the next five years. What you will be doing: Key responsibilities As a Data Analytics Manager, your role will encompass: Deliver the highest standards of quality on Data marketing projects Pilot multidisciplinary teams (consultants, data scientists, data analysts, software engineers, media traders) Develop robust, industry-leading measurement and analytics projects that enable clients with visibility across physical and digital customer journeys (online and offline) Planning, leading and delivering advanced analytics strategy and solutions for clients including e-commerce, 3rd party tool implementations, and advanced modeling. Identify and support the delivery of suitable statistical data analysis techniques, to provide recommendations for clients which exceed performance expectations and maximizes ROI Explore automation techniques that create efficiencies and improve ROI (both internally and for clients) such as scripting, tool development or better client reporting methods Act as an internal consultant on analytics for significant projects, helping other teams to shape the very best solutions Lead through the 'pitch ownership' and by taking an 'analytics lead' role on new business pitches Data Marketing and Analytics leadership Lead data analytics development, defining and communicating a clear strategy for the team and the value it will add to the agency Work together with the data consultants to champion analytics development and associated platforms on three fronts - internally to the agency, externally to clients and to represent Artefact's position to the wider marketing community Lead and develop roadmaps for our analytics offering, process, and techniques and develop best practice documentation Develop review and sign off processes to ensure analytics work is always of the highest possible quality Responsible for Artefact being known as exceptional in analytics in the wider market. Actively seek to build Artefact's profile within the digital marketing community. Qualifications: Education & experience required Core requirements 5+ years of hands-on experience in a data-driven environment. Strong expertise in at least one of the following domains: - Dashboarding & Data Visualization: Power BI, Looker, Tableau, or Superset. - Analytics Engineering: dbt, with experience on BigQuery, Snowflake, or Databricks. - Marketing Analytics & Measurement: CDP platforms (Treasure Data, Hightouch, Tealium), MMM, attribution, clean rooms. - Low-Code / No-Code Data Science: Dataiku, Copilot Studio, or similar platforms. Solid foundation in SQL and Python. Familiarity with Git and software engineering fundamentals (versioning, testing, code quality). Experience working in cloud environments (GCP, Azure, or AWS).

Requirements

• Experience with generative AI applied to analytics (MCP for BI, conversational data interfaces), exposure to multiple domains above, knowledge of statistics and machine learning fundamentals.
• Beyond technical expertise, we value: intellectual curiosity, pragmatism and creativity, ability to bridge business and technical teams, autonomy and reliability, and clear communication to build client trust.
• Our recruitment process
• HR call
• Technical Interview
• Use Case Interview
• Fit Interview

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