{"id":2007210,"url":"https://alion.io/job/espritek-analytics-engineer","title":"Analytics Engineer","company":{"id":3908532,"name":"Espritek","domain":"espritek.com","url":"https://alion.io/company/espritek","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":43000,"max_usd":79000,"period":"year","method":"role_country_seniority_unknown","sample_n":57},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon 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équipe Data dédiée aux usages digitaux en magasin d’un grand acteur international du retail.\nL’équipe a pour objectif d’exploiter la donnée afin d’améliorer l’efficacité des équipes opérationnelles en magasin et de leur permettre de prendre de meilleures décisions.\nVous interviendrez sur l’ensemble de la chaîne de transformation et de modélisation de la donnée, avec un rôle fortement orienté Analytics Engineering.\nVos principales responsabilités :\n• Automatiser et industrialiser les pipelines de transformation de données alimentant les dashboards, analyses Data et modèles IA ;\n• Construire et modéliser la semantic layer sur des domaines métier notamment liés à la Supply Chain et à la Production ;\n• Maintenir, optimiser et repenser les datasets et pipelines existants afin de répondre à de nouveaux cas d’usage ;\n• Construire des datasets robustes, fiables et facilement exploitables ;\n• Garantir la qualité des données exposées ;\n• Participer aux choix techniques et à l’évolution de la stack Data ;\n• Intégrer les enjeux de data lineage, de gouvernance et de documentation ;\n• Contribuer aux communautés Analytics Engineering et Data Engineering.\nEnvironnement technique :\nAWS, Databricks, Glue, S3, dbt, Airflow, SQL, Python, Scala, PySpark, Great Expectations, Git, GitHub, CI/CD, Make.\nProfil recherché\nVous justifiez d’au moins 3 ans d’expérience en tant qu’Analytics Engineer ou Data Engineer, ou d’une expérience significative en Data Analysis complétée par de solides compétences en Data Engineering.\nVous maîtrisez particulièrement dbt et Apache Airflow et possédez une expérience concrète sur Databricks ainsi qu’en SQL et/ou Python.\nVous êtes à l’aise avec la modélisation de données et connaissez des approches telles que Kimball, Data Vault ou OBT.\nVous avez déjà travaillé sur un environnement Cloud AWS, GCP ou Azure et comprenez les problématiques de performance, d’industrialisation et de fiabilité des pipelines Data.\nVous maîtrisez les bonnes pratiques de développement : Git/GitHub, CI/CD, documentation et qualité de code.\nVous comprenez les enjeux de data lineage, de gouvernance et de qualité des données.\nUn bon niveau d’anglais est nécessaire pour évoluer dans un environnement international.\nLa connaissance de Spark, Tableau, Great Expectations ou d’outils de la Modern Data Stack tels que Polars, DuckDB, Malloy ou MetricFlow constitue un plus.","description_format":"text","description_chars":2451,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-07T12:33:56Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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