Technical Architect - Data - Azure

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Role: Architect - Data (Azure)

Experience: 7-14 Years

Location: Mumbai/Bangalore/Trivandrum

Must have skills:

• Minimum 5 end to end AWS Data Engineering project implementation engagement experience

• Profound knowledge and expertise in Microsoft Azure, including Azure Data services like Azure SQL Database, Azure Data Lake Storage, Azure Synapse, Azure Databricks, Azure Data Factory etc.

• Strong skills in data modeling, data warehousing, and data architecture to design efficient and scalable data solutions.

• Proficiency in data integration techniques, ETL processes, and data pipeline development using Azure services.

• In-depth understanding of data governance principles, data security, and compliance requirements (e.g., GDPR, HIPAA), and the ability to implement these in Azure environments.

• Experience with database management systems, both relational and NoSQL, and the ability to choose the right storage solutions for different data types.

• Proficiency in SQL for querying and working with relational databases, as well as knowledge of NoSQL databases

• Familiarity with data analysis tools and reporting platforms such as Power BI, Tableau, or similar.

• Strong programming skills in languages like Python, Java, or C# for scripting, automation, and data manipulation.

• Extensive experience in data migration, including migrating data from on-premises environments to Azure and from one cloud platform to another.

• The ability to manage data-related projects, work collaboratively with cross-functional teams, and meet project deadlines

• Strong documentation skills for creating clear architectural documents and excellent communication skills for conveying complex technical concepts to non-technical stakeholders

Good to have skills:

• Relevant Microsoft Azure certifications, such as Azure Data Engineer or Azure Solutions Architect, can enhance your credibility.

• Knowledge of big data technologies like Hadoop, Spark, and Kafka for handling large datasets.

• Experience in PowerApps

• Familiarity with machine learning concepts and Azure Machine Learning for implementing data-driven models.

• Experience with DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines for data solutions.

• Understanding of real-time data processing and streaming technologies, such as Azure Stream Analytics.

• Skills in advanced analytics, data mining, and statistical analysis is good to have.

• Experience of data migration from AWS to Azure cloud is good to have

• Knowledge of Lakehouse patterns, Delta Lake / Iceberg / Parquet formats.

• Understanding of Azure infrastructure - Networking, Security, Virtual Networks, Key Vault and Monitoring

Role & Responsibilities:

• Designing and implementing data architecture in Azure, taking into account the organization's data requirements and future scalability.

• Developing the data integration solutions to bring data from various sources into Azure, ensuring data quality and consistency.

• Choosing and implementing appropriate Azure data storage solutions for different data types and optimizing for performance and cost.

• Implementing data processing solutions using Azure services, optimizing for performance and scalability.

• Planning, executing, and overseeing data migration projects, including migrations from on-premises environments to Azure and between different cloud platforms.

• Establishment and enforcement of data governance policies, ensuring data is compliant with regulations and industry standards.

• Monitoring data solutions for performance and cost, making necessary adjustments for optimization.

• Create data models as per client solution needs

• Documentation for data architecture and solutions and provide training to team members and stakeholders.

• Collaboration with cross-functional teams, including data engineers, data scientists, and business stakeholders, to ensure data solutions meet business needs.

• Managing data-related projects, including scoping, planning, execution, and data migration, while adhering to project timelines and budgets.

• Communicate with non-technical stakeholders to understand their data requirements and convey the benefits of data solutions, including migration strategies