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Data Engineer creating data pipelines for Santander's card transactions. Collaborating with an agile team in strategic projects involving Databricks and PySpark.
About the role
- Définir, concevoir et valider l’architecture Data (Data Lake, Data Warehouse, Data Mesh) pour les projets clients.
- Garantir la cohérence, la sécurité et la scalabilité des solutions mises en place.
- Concevoir et développer des pipelines complexes et hautement performants (batch & temps réel).
- Intégrer, transformer et orchestrer des données issues de multiples sources hétérogènes (APIs, systèmes legacy, bases SQL/NoSQL, fichiers massifs).
- Mettre en place monitoring, logging et optimisation des coûts.
- Être le référent technique et le mentor des Data Engineers et développeurs ; diffuser standards et bonnes pratiques (CI/CD, sécurité, code review).
- Collaborer avec Data Scientists, Analystes et Architectes ; contribuer à l’intégration et à l’industrialisation des modèles analytiques.
- Participer aux comités techniques et décisions stratégiques Data.
Requirements
- Expérience confirmée (7+ ans) en Data Engineering ou rôle équivalent, dont plusieurs années en tant que référent technique.
- Expertise technique : Python, SQL avancé, Spark, Bash ; Scala/Java (souhaité).
- Orchestration : Airflow, dbt ou équivalents.
- Bases de données relationnelles et NoSQL : Snowflake, BigQuery, MongoDB, Cassandra…
- Cloud : AWS, Azure, GCP avec forte compétence sur les services Data.
- Maîtrise des environnements CI/CD, Git, monitoring et sécurité.
- Bonne compréhension des architectures : Data Lake, Data Warehouse, Data Mesh, temps réel/streaming.
- Qualités recherchées : leadership technique, capacité d’analyse, autonomie, rigueur, pédagogie et curiosité.
- Expérience en mentorat et diffusion des bonnes pratiques.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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