Senior Data Engineer: Python, AWS & ML Pipelines (Production)

Lever, Inc.; France; Hybride; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Flexible working arrangements

Career growth opportunities

Professional development

Résumé du poste

Lever, Inc. is seeking a Senior Data Engineer based in France to build and operate large-scale data and ML pipelines in a production environment.

You will work across data engineering, cloud infrastructure, and ML operations to turn models into reliable production workflows with a strong emphasis on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure. You will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions,

Qualifications

• Strong experience with Python for data engineering and production systems.
• Proven track record building data pipelines and ML pipelines in production.
• Hands-on with Apache Airflow for workflow orchestration.
• Experience with AWS Glue, Step Functions, and SageMaker.
• Solid AWS cloud experience and scalable production environments.
• Familiar with monitoring/observability tools (nice-to-have).

Responsabilités

• Build and operate large-scale data and ML pipelines in production.
• Develop ETL and data-processing workflows using Python.
• Design and orchestrate workflows with Airflow and Step Functions.
• Use AWS Glue for data processing and pipeline execution.
• Support deployment and operation of ML models with SageMaker.
• Collaborate with Data Scientists and ML Engineers to productionize models.
• Monitor pipeline health and improve reliability and performance.
• Contribute to architectural decisions across the data platform.

Connaissances

Python

Data engineering

ML pipelines

Airflow

AWS

Troubleshooting

Team collaboration

English communication

Cloud computing

Outils

Apache Airflow

AWS Glue

AWS Step Functions

AWS SageMaker

Description du poste

Lever, Inc. is seeking a Senior Data Engineer based in France to build and operate large-scale data and ML pipelines in a production environment.

You will work across data engineering, cloud infrastructure, and ML operations to turn models into reliable production workflows with a strong emphasis on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure. You will collaborate closely with Data Scientists and ML Engineers to productionize forecasting and data-driven solutions,