EY - GDS Consulting - AI and DATA - Azure Architect - Manager
Job description
At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
Azure Architect - Manager
Overview
As a Enterprise Data Architect you will be responsible for designing, developing, and maintaining an organization's data architecture. Work closely with business stakeholders to understand their data needs and translate them into technical requirements and also oversee the implementation of data management solutions and ensure that they meet the organization's long-term goals.
Duties and Responsibilities
- Develop and maintain the organization's data architecture roadmap. Designing and developing data architecture solutions that are scalable, reliable, and high-performing
- Design and implement data management solutions, including data warehouses, data lakes, and data governance frameworks.
- Develop data standards and policies to ensure data quality and consistency.
- Collaborate with business stakeholders to understand their data needs and translate them into technical requirements.
- Design and implement data integration solutions to connect disparate data sources.
- Develop and maintain data models to represent the organization's data.
- Monitor and evaluate the performance of the data architecture and make recommendations for improvement.
- Stay up-to-date on the latest data management technologies and trends.
- Manage and mentor a team of data architects and data analysts.
- Developing and implementing data security and privacy policies, and ensuring compliance with relevant regulations such as GDPR and HIPAA.
- Building data pipelines and data processing workflows using Azure services such as Azure Data Factory, Azure Databricks, and Azure Stream Analytics.
- Evaluating and selecting appropriate data storage technologies such as Azure SQL Database, Azure Cosmos DB, and Azure Data Lake Storage.
- Troubleshooting data-related issues and providing technical support to data users.
- Keeping up-to-date with the latest trends and developments in data architecture, and making recommendations for improvement.
- Coordination and interaction with multiple teams for smooth operations.
Required Skills and Qualifications
- Bachelor's degree in computer science, information technology, or a related field.
- Proven experience as a Technical / Data Architect
- 9-10 years of overall product / solutions development experience
- Hands-on experience with software / product architecture, design, development, testing and implementation
- Excellent communication skills
- Problem-solving aptitude
- Organizational and leadership skills
- Agile development methodology
- Understanding of strategic development / deployment methodologies and techniques
- Source control (Git / VSTS)
- Continuous Integration / continuous deployment
- Information security
- Hands on Experience of Cloud based (Azure) product / platform development and implementation
- Worked on and delivered at least 5 + Cloud based solutions
- Good Experience in designing and working with Data Lakes, Data Warehouses and ETL tools
- Expertise in Azure Data Analytics having thorough understanding of Azure Data Platform tools
- Hands-on experience and good understanding of Azure services like : Data Factory, Data Bricks, Synapse, Data Lake Gen2, Stream Analytics, Azure Spark, Azure ML, SQL Server DB, Cosmos DB
- Experience with data visualization and reporting tools.
- Hands on experience in Information management and Business Intelligence projects, handling huge client data set with functions including transfer, ingestion, processing, analysing and visualization
- Excellent communication and problem-solving skills, and be able to work effectively in a team environment
- Strong understanding of data management principles and best practices.
- Experience with data modelling, data warehousing, data integration, and data governance.
- Excellent communication and collaboration skills.
- Strong analytical and problem-solving skills.
- Ability to work independently and as part of a team.
- Experience with big data technologies.
- Experience with machine learning and artificial intelligence.
- Experience with Agile methodologies.
EY | Building a better working world
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