Experteer Overview
As Lead Data Architect Azure at NTT DATA, you will shape data platforms for clients using Azure data and AI services.
You will lead Azure data projects, mentor engineers and collaborate with cross-functional teams to deliver scalable data lake solutions.
You will apply well-architected and cloud adoption frameworks to design robust architectures and guide stakeholders through technical tradeoffs.
This role offers impact across client design workshops, skill development, and the Azure Center of Excellence.
Responsibilities
Manage Key Clients
Manage relationships with Microsoft
Manage the Azure Center of Excellence
Lead Data & Analytics Azure projects
Support Recruitment
Support Value Proposition
Support development of skills and capabilities
Design Data Platform using Azure data & AI services (e.g., Synapse, Data Factory, Data Lake Gen2, Stream Analytics, Purview)
Design operations architecture and performance engineering for large-scale data lakes
Apply Microsoft Well Architected Framework (WAF) and Cloud Adoption Framework (CAF)
Create and maintain optimal data pipeline architecture using Azure services or data management technologies (e.g., Talend, Informatica)
Participate in client design workshops and provide tradeoffs and recommendations
Mentor other engineers in coding best practices and problem solving
Qualifications
Proven experience in data analytics, preferably in consulting
Minimum 5 years managing BI/data analysts up to senior level
Azure cloud native environment experience
Experience and knowledge of big data architectures, cloud and on-premise
Azure infrastructure and networking experience
Experience with Azure Load & Ingest: Event Hub, Data Factory, Databricks
Azure storage: Data Lake Gen1/Gen2, Delta Lake
Azure processing/serving: Synapse, Databricks, Stream Analytics
Experience delivering proofs-of-concept to address business needs
Experience migrating workloads from on-prem to cloud
Experience monitoring distributed infrastructure with Azure tools or CloudWatch, Prometheus, ELK stack
Experience with Agile/Kanban methods
Strong data manipulation and BI tool skills
Solid stakeholder management with top management
Proactive, problem-solving, cross-functional leadership in a collaborative role
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