Senior Data Engineer: Python, AWS & ML Pipelines

Lever, Inc.; Schweiz; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Benefits dieser Stelle

Collegial culture

Agile environment

Learning opportunities

Career growth

Business travel potential

Flexible work arrangements

Healthcare benefits

Zusammenfassung

Lever, Inc. in Switzerland seeks a Senior Data Engineer to build and operate production-grade data and ML pipelines.

You will work across data engineering, cloud infrastructure, and MLOps to productionize models, with strong emphasis on Python, AWS, ETL, and scalable ML infrastructure. Collaborating with Data Scientists and ML Engineers in distributed Agile teams, you will improve reliability and performance of pipelines, contribute to architectural decisions, and continue expanding cloud and ML

Qualifikationen

• Strong Python skills applied to data engineering and production systems.
• Experience building/maintaining data pipelines and ML pipelines in production.

Aufgaben

• Build, maintain, and improve production-grade data and ML pipelines.
• Develop ETL and data-processing workflows using Python.
• Design and orchestrate workflows with Apache Airflow and AWS Step Functions.
• Use AWS Glue for data processing, transformation, and orchestration.
• Support deployment of ML models via AWS SageMaker.
• Collaborate with Data Scientists and ML Engineers to productionize solutions.
• Monitor pipeline health, troubleshoot production issues, and improve reliability.
• Contribute to architectural decisions for the data platform and ML infra.
• Collaborate with distributed Agile teams to improve engineering practices.

Kenntnisse

Python

Data pipelines

ML pipelines

Cloud infrastructure

Airflow orchestration

SageMaker usage

Tools

Apache Airflow

AWS Step Functions

AWS Glue

AWS SageMaker

Jobbeschreibung

Lever, Inc. in Switzerland seeks a Senior Data Engineer to build and operate production-grade data and ML pipelines.

You will work across data engineering, cloud infrastructure, and MLOps to productionize models, with strong emphasis on Python, AWS, ETL, and scalable ML infrastructure. Collaborating with Data Scientists and ML Engineers in distributed Agile teams, you will improve reliability and performance of pipelines, contribute to architectural decisions, and continue expanding cloud and ML