Data Engineer - Manager/Specialist
On-siteParis, Île-de-France, France
Job Summary
Design, implement, and test data pipelines, ETL/ELT processes, and storage solutions for structured and unstructured data using big data technologies like Spark and Kafka. Build scalable, reliable pipelines while collaborating with data scientists, modelers, and architects to ensure efficient data flows and optimal storage. Automate provisioning, deployments, and environment management for data platforms, creating APIs and services for internal and external consumers. Coordinate with integration teams for smooth data ingestion and ensure solutions meet requirements for scalability, performance, and governance. Lead a team to create technology products that enhance customer experiences, leveraging deep technical expertise across multiple cloud platforms and programming languages.
Required Qualifications
- Hands-on experience with ETL/ELT design and implementation
- Familiarity with big data ecosystems (e.g., Spark, Hadoop, Kafka, Flink)
- Experience with one or more cloud platforms (Azure, AWS, GCP) and modern data engineering tools (e.g., Databricks, Snowflake, BigQuery, Synapse)
- Proficiency in programming languages such as Python, Java
- Solid understanding of SQL and experience with both relational and non-relational databases
- Experience with data modeling, schema design, and data partitioning strategies
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
- 7+ years of professional experience in data engineering or related roles
- Strong teamwork, communication, analytical thinking, and problem-solving skills
- Fluent in English, both spoken and written
- Curiosity and drive to continuously learn, adapt, and share knowledge
Desired Qualifications
- Knowledge of workflow orchestration tools (e.g., Airflow, Data Factory) is a plus
- Some exposure to AI and agentic platforms, and familiarity with cloud providers' managed AI services (e.g., Azure AI Foundry, AWS Bedrock, Vertex AI), is a plus
- Some exposure to DevOps practices and infrastructure (e.g., IaC, containers, cloud infrastructure) is a plus
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