Experteer Overview
In this role you will design and maintain data pipelines that power enterprise analytics and ML model consumption. You will work closely with data architects and analysts to translate business needs into scalable data solutions across cloud and on‑prem environments. You help ensure data quality, reliability, and performance while optimizing pipelines for speed and cost. This position offers impact across reporting, analytics, and operational intelligence within a mission-driven, fast-paced company.
Retribuzione / Benefits
* Design, implement, and maintain robust data pipelines for analytics, reporting, and ML consumption
* Ensure reliable data ingestion, transformation, and delivery across cloud and on-prem environments
* Automate workflows, monitor data health, and address bottlenecks or failures
* Integrate structured and unstructured data from diverse sources into unified data stores
* Optimize data workflows for speed, efficiency, and cost with modern tools and cloud-native capabilities
* Collaborate with data architects and analysts to align solutions with business goals
* Partner with cross-functional teams to meet evolving data needs
* Contribute to engineering standards, documentation, and reusable components
* Engage in peer reviews and continuous learning to foster a high-performance culture
Responsabilità
* Bachelor in Computer Science or related field
* 5+ years of experience as Data Engineer
* Advanced proficiency in SQL, Python and Spark
* Experience with Microsoft Fabric components (OneLake, Dataflows, Power BI)
* Expertise with Azure Databricks for scalable data workloads
* Advanced proficiency in data modeling (conceptual, logical, physical)
* Knowledge of data governance (quality, metadata, MDM)
* Microsoft Fabric and Databricks certifications strongly preferred
* Proficiency in English (spoken and written)
* Ability to coordinate tasks, projects, and priorities
Requisiti fondamentali
* meal vouchers
* corporate gym
* regional bonus
* longevity program
* health insurance (FASA)
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