Senior Data Engineer (Python / AWS / ML Pipelines)

About the role

We are looking for a Senior Data Engineer to build and operate large‑scale data and machine‑learning pipelines in a production environment. You will work across data engineering, cloud infrastructure and ML operations, collaborating closely with Data Scientists and ML Engineers.

Key responsibilities

• Build, maintain, and improve production‑grade data and machine‑learning pipelines supporting forecasting and data‑driven decision‑making.
• Develop ETL and data‑processing workflows using Python that are scalable, reliable and maintainable.
• Design and orchestrate workflows with Apache Airflow and AWS Step Functions, and use AWS Glue for data transformation.
• Support deployment and operationalisation of ML models on AWS SageMaker.
• Monitor pipeline health, troubleshoot issues and implement improvements for reliability and performance.
• Contribute to architectural decisions and collaborate with distributed Agile teams.

Required profile

• Strong professional experience with Python in data‑engineering and production systems.
• Proven experience building and maintaining data or ML pipelines in production.
• Hands‑on experience with Apache Airflow, AWS Step Functions and AWS Glue.
• Experience deploying and supporting models using AWS SageMaker.
• Ability to work independently and collaboratively in distributed cross‑functional teams.
• Excellent written and verbal English communication skills.

Required skills

• Python
• AWS (Step Functions, Glue, SageMaker)
• Apache Airflow
• ETL workflow development
• Machine‑learning pipeline orchestration
• GCP (optional)

What we offer

• Collegial working environment with shared responsibility and decision‑making.
• Agile culture encouraging ideas and technical influence.
• Supportive approach to learning from mistakes and continuous improvement.
• Opportunities to work on varied projects and broaden technical experience.
• Ongoing training, mentoring and professional development.
• Career growth, exposure to new technologies and challenges.
• Possibility of business travel and flexible working arrangements.