Digital Solution Architect

Overview

As Digital Solution Architect, you will design and deploy modern data pipelines and cloud-based platforms to empower data analytics across projects in the Digital Lab. You will integrate external data sources, manage data lakes and warehouses, and support data science initiatives with reliable data access. You will collaborate with Business and R&D, ensuring security and governance while delivering PoC and MVPs in Agile teams. This role offers impactful work shaping data infrastructure, enabling advanced analytics at scale, and driving cloud-first data initiatives. You will work in a cross-functional environment to turn data into actionable insights.

Responsabilità

• Design, develop and deliver reliable modern data pipelines for data projects
• Implement batch data ingestion, processing and transformation
• Implement streaming data ingestion, processing and transformation
• Provide access to datasets for Data Science team
• Manage data and metadata in Big Data Warehouse and data stores
• Design, administer and maintain Data Lake for analytics
• Develop and deliver data integration components
• Operate data pipelines and cloud resources during failures and bugfixes
• Deploy, configure and monitor Cloud Data Platform infrastructure
• Collaborate with Data Architect and Data Scientists
• Support ML and predictive models deployment in the cloud
• Facilitate and orchestrate Cloud, IoT and Analytics use cases
• Work in Agile teams to deliver PoC/MVP projects
• Familiar with web development, Microsoft stack

Requisiti fondamentali

• Master's Degree in Computer Science or equivalent
• Minimum 3 years of experience with Big Data projects (HDFS, Hadoop, Spark, Spark Streaming, Hive, HBase)
• Minimum 3 years of experience with Batch and Streaming pipelines in Microsoft Azure and Spark
• Analytical problem solving
• Strong communication in multicultural environments
• Logical thinking and teamwork
• Azure data services (Data Factory, Databricks, Data Lake Store, SQL Database, HDInsight)
• Experience with Spark and SQL for big data transformations
• Serverless: Azure Functions, AWS Lambda