Python Engineer – ML/Data Pipelines
This a Full Remote job, the offer is available from: Europe
This is a remote position.
About the Project
Currently, we are looking for a Python Engineer – Data Pipelines for our key client, an innovative company specializing in data-driven solutions. Focused on leveraging technology, people, and processes, the company develops and optimises software, data infrastructure, and AI-powered tools for businesses across industries. With a collaborative, agile environment, it emphasizes continuous learning, career growth, and remote work flexibility.
This role focuses on building and maintaining data pipelines that operationalize PoC solutions developed by a team of data scientists. These PoCs—often related to marketing segmentation or attribute enrichment—are transformed into scalable, production-ready pipeline components. You will work in a team of 5: project lead, 3 data/software engineers, and 1 QA.
Your Duties:
As a Python Engineer – ML/Data Pipelines , you will be responsible for:
- Developing and maintaining scalable data pipelines to support production deployment
- Translating Python-based scripts from data scientists into robust, maintainable pipeline components
- Implementing workflow orchestration using Kubeflow or similar tools (Airflow, Argo, MLflow, etc.)
- Collaborating with data scientists to understand PoC requirements and convert them into production workflows
- Optimizing pipelines for performance, reliability, and efficient resource usage
- Debugging, monitoring, and resolving pipeline issues in production environments
- Contributing to continuous improvement of tooling, workflows, and best practices
- Supporting cloud-based deployments and infrastructure (any major cloud platform)
Requirements
• 4+ years of Python development experience (APIs, automation, backend systems, or pipeline work).
• Strong understanding of data workflows, data processing, or data management.
• Experience with workflow orchestration tools such as Kubeflow, Airflow, Argo, Prefect, or MLflow.
• Knowledge of containerization best practices (e.g., Docker); Kubernetes is a plus but not required.
• Familiarity with cloud environments (GCP, AWS, or Azure all acceptable).
• Strong debugging, problem-solving, and communication skills.
• Experience collaborating in cross-functional engineering teams.
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• English language proficiency at B2 level or higher.
• Nice to have:
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) not required.
• Experience with CI/CD pipelines and DevOps tools.
• Exposure to Kubernetes.
• Experience working with databases especially Snowflake and integrating them into data workflows.
Salary: EUR 3000This offer from "Gegidze" has been enriched by Jobgether.com and got a 78% flex score.
Apply tot his job
Apply To this Job
This is a remote position.
About the Project
Currently, we are looking for a Python Engineer – Data Pipelines for our key client, an innovative company specializing in data-driven solutions. Focused on leveraging technology, people, and processes, the company develops and optimises software, data infrastructure, and AI-powered tools for businesses across industries. With a collaborative, agile environment, it emphasizes continuous learning, career growth, and remote work flexibility.
This role focuses on building and maintaining data pipelines that operationalize PoC solutions developed by a team of data scientists. These PoCs—often related to marketing segmentation or attribute enrichment—are transformed into scalable, production-ready pipeline components. You will work in a team of 5: project lead, 3 data/software engineers, and 1 QA.
Your Duties:
As a Python Engineer – ML/Data Pipelines , you will be responsible for:
- Developing and maintaining scalable data pipelines to support production deployment
- Translating Python-based scripts from data scientists into robust, maintainable pipeline components
- Implementing workflow orchestration using Kubeflow or similar tools (Airflow, Argo, MLflow, etc.)
- Collaborating with data scientists to understand PoC requirements and convert them into production workflows
- Optimizing pipelines for performance, reliability, and efficient resource usage
- Debugging, monitoring, and resolving pipeline issues in production environments
- Contributing to continuous improvement of tooling, workflows, and best practices
- Supporting cloud-based deployments and infrastructure (any major cloud platform)
Requirements
• 4+ years of Python development experience (APIs, automation, backend systems, or pipeline work).
• Strong understanding of data workflows, data processing, or data management.
• Experience with workflow orchestration tools such as Kubeflow, Airflow, Argo, Prefect, or MLflow.
• Knowledge of containerization best practices (e.g., Docker); Kubernetes is a plus but not required.
• Familiarity with cloud environments (GCP, AWS, or Azure all acceptable).
• Strong debugging, problem-solving, and communication skills.
• Experience collaborating in cross-functional engineering teams.
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• English language proficiency at B2 level or higher.
• Nice to have:
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn) not required.
• Experience with CI/CD pipelines and DevOps tools.
• Exposure to Kubernetes.
• Experience working with databases especially Snowflake and integrating them into data workflows.
Salary: EUR 3000This offer from "Gegidze" has been enriched by Jobgether.com and got a 78% flex score.
Apply tot his job
Apply To this Job