Senior Data Engineer: Python, AWS & ML Pipelines

Lever, Inc.; México; A distancia; MXN 900.000 - 1.300.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Collegial environment

Agile culture

Learning and development

Career growth

Flexible remote work

Descripción de la vacante

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

The role focuses on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure. You will collaborate with Data Scientists to productionize forecasting and data-driven solutions, improve reliability and observability of pipelines, and contribute to architecture within distributed Agile teams.

Formación

• Strong professional experience with Python in data engineering and production systems.
• Proven experience building and maintaining data pipelines and ML pipelines in production.
• Hands-on experience with Apache Airflow for workflow orchestration.
• Practical experience with AWS Step Functions and AWS Glue.
• Experience deploying and supporting ML models using AWS SageMaker.

Responsabilidades

• Build, maintain, and improve production-grade data and ML pipelines.
• 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 of ML models using SageMaker.
• Collaborate with Data Scientists and ML Engineers to productionize solutions.
• Monitor pipeline health and improve reliability, scalability, and performance.
• Contribute to architectural decisions for data platform and ML infrastructure.

Conocimientos

Python

Data engineering

ML pipelines

Troubleshooting

English communication

Herramientas

Apache Airflow

AWS Step Functions

AWS Glue

AWS SageMaker

Descripción del empleo

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

The role focuses on Python, AWS, ETL, workflow orchestration, and scalable ML infrastructure. You will collaborate with Data Scientists to productionize forecasting and data-driven solutions, improve reliability and observability of pipelines, and contribute to architecture within distributed Agile teams.