ph3About the role /h3 /brpThis role combines data platform engineering and MLOps responsibilities, supporting both reliable analytical data flows and production-ready machine learning solutions. The person will maintain and improve ETL pipelines, support the data platform environment, and help deploy, monitor, and optimize machine learning models in production. The role requires close cooperation with Data Science, Engineering, BI, Risk, and IT teams to ensure that data and model processes are scalable, well-documented, stable, and aligned with business needs. /p /brh3Key Responsibilities /h3 /brpAs a Data Platform and MLOps engineer, you will be part of our Data Platform team and play an important role in our daily operations. Your responsibilities will include: /p /brul /brlipDeploy machine learning models into production environments and support their operational lifecycle. /p /li /brlipSupport cloud-based analytical, reporting, and machine learning infrastructure. /p /li /brlipCollaborate closely with Data Science, Engineering, Risk, BI, and IT teams to align data and model requirements with production standards. /p /li /brlipDevelop automation for model deployment, updates, scaling, and recurring data processing tasks. /p /li /brlipImplement monitoring for both data pipelines and machine learning models, including performance, availability, and quality checks. /p /li /brlipEnsure reliable operation and continuous development of the analytical data warehouse environment. /p /li /brlipDesign, maintain, troubleshoot, and optimize ETL/data pipelines supporting reporting, analytics, and machine learning use cases. /p /li /brlipEnsure timely and high-quality data availability for BI, Risk, Data Science, and other business stakeholders. /p /li /brlipIdentify, investigate, and resolve performance issues across data warehouse, ETL, and model deployment processes.



/p /li /brlipTroubleshoot, debug, upgrade, and improve existing software, pipelines, and deployment processes. /p /li /brlipGather and evaluate user feedback, recommend improvements, and execute enhancements. /p /li /brlipMaintain technical documentation for data processes, model deployments, configurations, and operational procedures. /p /li /br /ul /brh3Qualifications and Experience /h3 /brpWe are looking for someone who has: /p /brul /brlip2+ years of experience in data engineering and machine learning /p /li /brlipStrong bPython /b programming skills and intermediate SQL knowledge /p /li /brlipGood understanding of databases, data warehouse concepts, and ETL processes /p /li /brlipUnderstanding of machine learning lifecycle and model operationalization /p /li /brlipUsing LLM’s to generate and optimize code, ability to use AI platform features to enhance and speed up workflows /p /li /brlipKnowledge of DevOps practices, CI/CD pipelines, and version control /p /li /brlipExperience with cloud-based analytical and reporting solutions, preferably Azure /p /li /brlipFamiliarity with machine learning frameworks and tools such as scikit-learn and XGBoost /p /li /brlipFamiliarity with containerization technologies such as Docker /p /li /brlipAbility to monitor, troubleshoot, and optimize data pipelines, infrastructure, and deployed models /p /li /brlipExperience with software design, development, debugging, and documentation /p /li /brlipProficient English, B1/B2 level or higher. /p /li /br /ul /brh3What we Offer /h3 /brul /brlipA friendly and collaborative team culture /p /li /brlipThe opportunity to learn from experienced colleagues and grow within IT /p /li /brlipA modern technical environment with room for improvement and innovation /p /li /brlipA workplace where teamwork, curiosity, and continuous improvement are valued /p /li /br /ul /br /p #J-18808-Ljbffr

📌 Machine Learning Ops And Data Engineer (Málaga)
🏢 Avarda Group
📍 Málaga