Data ML Platform Engineer

April 15

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Xebia

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Xebia is a pioneering Software Engineering and IT consultancy company that specializes in digital transformation, agile transformation, cloud computing, data and AI, DevOps, and intelligent automation. The company focuses on creating digital leaders by leveraging advanced technology and providing strategic solutions to diverse industries, including Banking, Healthcare, Retail, and more. With a global presence and a strong partnership with GitHub and Google Cloud, Xebia provides end-to-end services that empower organizations to maximize their technology potential and drive innovation.

IT Consultancy • Continuous Delivery • Offshore Services • Deployment Automation • Digital Transformation

5001 - 10000 employees

🤝 B2B

💳 Fintech

📋 Description

• As a Data Engineer you will develop and deliver high-quality features for our client's new ML Platform • Part of the Data Foundation Team, focusing on creating and maintaining the Data Platform • Heavy hands-on code, translate code between languages and set up infrastructure components • Responsible for infrastructure design, build and deployment with a focus on distributed systems • Building and maintaining architecture patterns for data processing and integrations • Evaluating and translating technical design to workable solutions/code • Driving creation of re-usable artifacts • Establishing scalable, efficient, automated data processes • Working closely with analysts/data scientists to understand impact on downstream models • Writing efficient and well-organized software to ship products • Contributing to good software engineering practices across the team • Communicating clearly to technical and non-technical audiences • Defining data retention policies and monitoring performance

🎯 Requirements

• Ready to start immediately • 5+ years of hands-on experience in using Python, Spark • Experience in AWS Cloud usage and management • Experience with Databricks (Lakehouse, ML, Unity Catalog, MLflow) • Experience using various ML models and frameworks such as XGBoost, Lightgbm, Torch • Experience with orchestrators such as Airflow and Kubeflow • Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) • Fundamental understanding of Parquet, Delta Lake and other data file formats • Proficiency on an IaC tool such as Terraform, CDK or CloudFormation • Strong written and verbal English communication skill and proficient in communication with non-technical stakeholders.