Saint-Gobain | Azure Data Lake Senior Engineer

4 weeks ago


india Saint-Gobain Full time

1/ Azure Data Lake Architecture :

Architect, design, and implement scalable and efficient data solutions utilizing Azure Data Lake Storage and related services.

2/ ETL Pipeline Development:

Lead the development of end-to-end ETL pipelines, ensuring seamless data movement, transformation and loading within the Azure Data Lake environment.

3/ Data Modelling and Integration:

Design and implement effective data models and integration strategies to support business requirements and analytical needs.

4/ Azure Services Integration:

Integrate Azure Data Lake with other Azure services, such as Azure Data Factory, Azure Databricks, and Azure Synapse Analytics, to create comprehensive data processing workflows.

5/ Performance Optimization:

Optimize data storage, retrieval, and processing for maximum performance and efficiency within the Azure Data Lake ecosystem.

6/ Data Security and Governance:

Implement robust data security measures, including role-based access control (RBAC), encryption, and compliance with data governance policies.

7/ Collaboration:

Collaborate with cross-functional teams, data analysts, and business stakeholders to understand requirements and deliver effective data solutions.

8/ Monitoring and Maintenance:

Establish monitoring mechanisms and perform routine maintenance tasks to ensure the health and reliability of the Azure Data Lake environment.

9/ Documentation:

Create and maintain comprehensive documentation for data processes, architecture, and solutions within the Azure environment.

10/ Mentorship:

Provide mentorship and guidance to junior members of the data engineering team, fostering a culture of continuous learning.

Requirements:

A/ Azure Expertise:

Proven experience in designing and implementing data solutions using Azure Data Lake Storage and related Azure services.

B/ Technical Skills:

Proficient in data modeling, ETL processes, and programming languages (e.g., Python, C#) within the Azure ecosystem.

C/ Big Data Technologies:

Experience with Big Data technologies such as Apache Spark and Hadoop within the Azure environment.

D/ Problem Solving:

Strong analytical and problem-solving skills, with the ability to address complex data engineering challenges in the Azure Data Lake context.

E/ Communication Skills:

Excellent communication and collaboration skills, with the ability to convey technical concepts to non-technical stakeholders.

F/ Leadership:

Proven leadership experience in guiding and mentoring a team of data engineers in an Azure-centric environment.



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