Digital Solution Architect
Pubblicato il 16-09-2026 - Bridgestone in Lazio
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