{"id":2007253,"url":"https://alion.io/job/ucase-consulting-data-engineer-senior","title":"DATA ENGINEER SENIOR","company":{"id":3908452,"name":"Ucase Consulting","domain":"ucase-consulting.com","url":"https://alion.io/company/ucase-consulting","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"freelance","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":{"min":40000,"max":45000,"currency":"EUR","period":"year","gross":null,"usd_annual":50637},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"Terraform","optional":false},{"name":"Trino","optional":false}],"status":"live","first_seen_at":"2026-10-05T07:55:18Z","employer_posted_date":null,"last_verified_at":"2026-10-05T07:55:18Z","board_verified":false,"closed_at":null,"days_open":12,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":12},"description":"🚀 Data Engineer Senior – Big Data / Lakehouse / AWS\nNiveau : Senior\nExpérience : 8 ans minimum en Data Engineering\nDémarrage souhaité : ASAP\nDurée : 12 mois, renouvelable\nRythme : 5 jours/semaine\nTélétravail : 3 jours/semaine\n🎯 Contexte de la mission : \nDans le cadre du renforcement de son pôle Data Services, notre client recherche un Data Engineer Senior pour accompagner la conception, l’industrialisation et l’évolution de ses solutions Data.\nLe consultant interviendra sur des sujets à forte dimension Data Engineering, Big Data et Lakehouse, avec notamment des problématiques d’architecture, de modélisation, d’optimisation des pipelines et d’industrialisation des traitements.\nIl contribuera également à l’évolution de la stratégie Lakehouse du client et devra être capable d’accompagner techniquement des profils plus juniors.\n\n🔎 Missions\nConcevoir, développer et optimiser des pipelines de données à grande échelle\n\nMettre en œuvre des flux batch, streaming et ingestion via API\n\nStructurer les données selon une architecture Médaillon (Bronze / Silver / Gold)\n\nDévelopper et industrialiser les transformations avec DBT, Spark et Iceberg\n\nContribuer à l’évolution et à l’optimisation de l’architecture Lakehouse\n\nDéployer et maintenir les pipelines dans un environnement AWS\n\nOrchestrer les workflows ETL / ELT via Airflow\n\nMettre en œuvre l’Infrastructure as Code avec Terraform\n\nParticiper à la mise en place et au maintien de l’observabilité et de la supervision des traitements\n\nDéfinir et mettre en œuvre les règles de Data Quality : tests, contrôles et validations automatisées\n\nParticiper à la gestion des incidents et à l’amélioration continue\n\nDocumenter les architectures, pi\n\nProfil recherché\n👤 Profil recherché\nNous recherchons un Data Engineer Senior avec 8 ans minimum d’expérience en Data Engineering, capable d’intervenir sur des environnements Big Data et Lakehouse complexes.\nLe profil devra impérativement maîtriser Spark, DBT, Iceberg, AWS et Terraform, avec une expérience concrète sur la conception, l’industrialisation et l’optimisation de pipelines de données à grande échelle.\nUne bonne maîtrise des services AWS tels que S3, Glue et EMR est attendue, ainsi qu’une capacité à travailler sur des sujets d’architecture, de modélisation et de Data Quality.\nLe candidat devra également être autonome, rigoureux et force de proposition, avec une bonne compréhension des enjeux métiers et une capacité à accompagner et faire monter en compétence des profils juniors.\nLa connaissance de Starburst / Trino, Datadog, Python, Airflow, Docker et Kubernetes sera un véritable plus.","description_format":"text","description_chars":2604,"description_truncated":false,"requirements":{"experience_years_min":null,"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":76,"band":"hot","label":"Hiring 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