Azure Data Architect
Pubblicato il 21-10-2026 - Ntt Data in Ala
Overview
As an Azure Data Architect at NTT DATA, you design and operalize secure, scalable data platforms that turn raw data into actionable insights.
You collaborate with business analysts and solution architects to translate use cases into data solutions for analytics and machine learning.
You'll build and optimize data pipelines for data lakes and analytics workloads, while championing simplicity, innovation, and cross-functional sharing.
This role sits at the intersection of Data Science and Data Engineering within a global, mixed Japanese–European environment and offers meaningful impact through data-driven decision making.
Responsabilità
Support customers in Big Data projects and define data needs with stakeholders.
Deliver data acquisition, transformation, cleansing, conversion, compression and loading into data lakes for analytics/ML.
Collaborate with business analysts and solution architects to shape use cases and outcomes.
Develop and share innovative, simple data solutions that address everyday issues.
Bridge Data Science and Data Engineering to align models with data prep and infrastructure.
Requisiti fondamentali
Cloud-native experience in at least one major public cloud (GCP/AWS/Azure); Azure experience preferred (5+ years).
Experience with Big Data architectures, both cloud and on-premise.
Azure infrastructure and network experience.
Proven ability to deliver PoCs addressing business needs using appropriate tools and data sources.
Experience migrating workloads from on-prem to cloud.
Monitoring distributed infrastructure via Azure tools or open-source options (Grafana, Prometheus).
Proficient in Java, Scala, Python, and shell scripting; strong SQL knowledge.
Experience with Agile methodologies and Kanban; leadership of mid-sized teams.
Hands-on with Apache Spark, Databricks, Azure Data Factory, Azure Synapse, and other Azure ETL/ELT tools.
Microsoft Certifications: Azure Data Engineer Associate or Azure Solutions Architect Expert.
Cross-functional collaboration
Continuous improvement mindset (Kaizen)
Problem solving and innovative thinking
Apache Spark
Databricks
Azure Data Factory