Glorious Insight - Lead Azure Data Engineer (8-10 yrs)

Company Description :

Glorious Insight is a company at the forefront of digital transformation, providing innovative solutions in Data & AI, Automation, Cloud, and Modern Apps.

With a client-centric approach and expertise in various industries like BFSI, Retail, Healthcare, and more, we deliver tailored solutions that drive sustainable growth.

Committed to sustainability, diversity, and ethical business practices, we aim to make a positive impact on society and the environment.

About the Job :

This is a full-time, on-site role located in Noida for a Lead Azure Data Engineer at Glorious Insight.

We are seeking a highly skilled and experienced individual to lead our data engineering efforts on the Azure platform.

The ideal candidate will have a strong understanding of data engineering principles, extensive experience with Azure data services, and a proven track record of delivering successful data solutions.

You will play a critical role in designing, building, and maintaining our data infrastructure, ensuring its scalability, reliability, and performance.

Responsibilities :

- Lead and mentor a team of data engineers, providing technical guidance, fostering collaboration, and promoting best practices.

- Design and implement robust and scalable data solutions on the Azure platform, including data lakes, data warehouses, and ETL pipelines.

- Develop and maintain ETL processes using Azure Data Factory, Azure Databricks, Azure Logic Apps, or other relevant Azure services.

- Design and implement data models that meet business requirements and ensure data integrity, including dimensional modeling and star schema design.

- Build and maintain data warehouses and data marts on Azure Synapse Analytics, Azure SQL Data Warehouse, or other appropriate Azure services.

- Enable data analytics by providing clean, reliable, and readily accessible data.

- Optimize data pipelines and data storage for performance and cost efficiency, including query optimization and index tuning.

- Troubleshoot data-related issues and provide support to data consumers.

- Collaborate with other teams, including business analysts, data scientists, and application developers, to understand data needs and deliver effective solutions.

- Stay up-to-date with the latest Azure data services and technologies and identify opportunities for improvement in our data infrastructure.

Qualifications :

Education : Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

Experience :

- 8+ years of experience in data engineering, with a significant portion focused on Azure data services.

- Prior experience leading a team is highly desirable.

Technical Skills :

- Strong understanding of data engineering principles and best practices.

- Extensive experience with Azure Data Factory, Azure Databricks (including Spark and Delta Lake), Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Blob Storage, Azure SQL Database, Azure SQL Data Warehouse, Azure Cosmos DB, Azure Logic Apps, Azure Functions.

- Proficiency in SQL (T-SQL, PL/SQL) and at least one programming language (e., Python, Scala, Java).

- Experience with data modeling techniques (e., Kimball methodology, Data Vault) and data warehousing concepts (e., star schema, snowflake schema).

- Knowledge of data governance and security best practices, including data masking, encryption, and access control.

- Experience with CI/CD pipelines for data engineering projects using Azure DevOps or similar tools.

- Familiarity with data virtualization tools (e., Denodo) is a plus.

- Experience with real-time data streaming technologies (e., Azure Event Hubs, Azure Stream Analytics, Kafka) is a plus.

- Knowledge of big data processing frameworks (e., Hadoop, Hive, Pig) is a plus.

- Familiarity with data quality management tools and processes.

- Experience with containerization technologies (e., Docker, Kubernetes) is a plus.

- Familiarity with Infrastructure as Code (IaC) tools (e., ARM templates, Terraform) is a plus.

- Experience with data visualization tools (e., Power BI, Tableau) is a plus