Senior Data Engineer - Python, AWS & ML Pipelines

Lever, Inc.; Australia; On-site; AUD 150,000 - 210,000; Full time

Benefits offered by this job

Flexible working arrangements

Career development and training

Business travel opportunities

Job summary

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

You will work across data engineering, cloud infrastructure, and ML operations to turn models into reliable production workflows, focusing on Python, AWS, ETL, and scalable ML infrastructure. Collaborate with Data Scientists to productionize forecasting and data-driven solutions.

Qualifications

• Proven experience building data/ML pipelines in production.
• Hands-on Airflow for workflow orchestration.
• Experience with AWS Step Functions and AWS Glue.
• Experience deploying ML models with AWS SageMaker.
• Strong AWS cloud experience in production environments.
• Experience with large-scale systems emphasizing reliability and performance.
• Excellent written and verbal English communication.
• Ability to work in distributed Agile teams.
• GCP experience is a plus.
• Familiarity with monitoring/observability tools is advantageous.

Responsibilities

• Build and operate production‑grade data and ML pipelines.
• Develop ETL workflows using Python for scalable pipelines.
• Design and orchestrate workflows with Airflow and AWS Step Functions.
• Use AWS Glue for data processing and pipeline execution.
• Deploy ML models using AWS SageMaker in production.
• Collaborate with Data Scientists and ML Engineers to productionize solutions.
• Monitor pipeline health and improve reliability, performance, and observability.
• Contribute to architectural decisions for the data platform and ML infra.
• Work with distributed, cross‑functional Agile teams.

Skills

Python

Data pipelines

Production systems

Distributed teams

Tools

Apache Airflow

AWS Step Functions

AWS Glue

AWS SageMaker

Job description

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

You will work across data engineering, cloud infrastructure, and ML operations to turn models into reliable production workflows, focusing on Python, AWS, ETL, and scalable ML infrastructure. Collaborate with Data Scientists to productionize forecasting and data-driven solutions.