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Bridgestone

Rome / Global

Digital Solution Architect

Job Description

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

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