Experteer Overview In this role you design, build, and operate scalable Databricks data platforms in Azure, enabling cross-functional teams to deliver data and AI solutions. You'll standardize practices, promote self-service capabilities, and coach engineers, analysts, and scientists to raise data maturity. You work at the Data u0026amp;
AI Center of Excellence, collaborating with architects, security, governance, and domain teams to balance autonomy with enterprise policies. You will drive platform reliability, cost efficiency, and developer experience, while sharing knowledge across the organization. Compensaciones / Ventajas
Design, build, and operate scalable Databricks platforms in Azure
Develop shared platform components: workspace standards, clustering, networking, integrations
Automate provisioning/configuration via IaC and CI/CD
Ensure platform reliability, performance, cost-efficiency, observability
Enable self-service data engineering with templates, libraries, and reference architectures
Define platform standards, guardrails, and best practices for ingestion,



transformation, and analytics
Provide technical consultancy to data engineers, analytics engineers, data scientists, and product teams
Deliver training, workshops, and onboarding materials; coach and mentor engineers
Contribute to documentation, communities, and data engineering guilds
Collaborate with data, security, governance, and architecture teams to align with enterprise policies
Foster Data u0026 AI engineering culture and continuous learning
Responsabilidades
~5+ years of experience in data platform engineering or data engineering in large-scale environments
~ Hands-on Databricks experience (data engineering, analytics, or platform administration)
~ Proficient in Python and SQL; familiarity with CI/CD practices
~ Solid understanding of data lake/lakehouse architectures, data ingestion and transformation patterns
~ Cloud-native data platforms experience; comfortable in an Azureenvironment;

📌 Data Engineer (Madrid)
🏢 Nn Group
📍 Madrid