Data Engineer at Snapnet Limited

Snapnet is a fast growing firm focused in developing industry specific solutions, Business consulting and Systems Integration with offices in Lagos and Abuja, Nigeria. We are committed to delivering first class innovation, quality and state of the art technology solutions to discerning clients both in the private and public sector. Our focus is the provision of Business and Information Technology solutions to drive the operations of organizations for growth and effectiveness. We have assisted our various clients improve organizational performance by combining the innovative use of technology with extensive business process experience in a range of industries to deliver solutions that help our clients achieve rapid and sustainable business advantage.

Job Description

• We are seeking a talented Azure Data Engineer to join our organization.
• As an Azure Data Engineer, you will be responsible for developing data pipeline solutions using Azure Data Factory, as well as integrating Azure Databricks functionalities and loading data into Azure SQL Database.
• You will also develop solutions to load data from Network Shared Folders into Azure Data Lake Gen 2.

Responsibilities:

• Design, develop, and maintain data pipeline solutions using Azure Data Factory.
• Collaborate with stakeholders to understand data integration requirements and translate them into scalable and efficient data pipelines.
• Implement data ingestion processes to load data from Network Shared Folders into Azure Data Lake Gen 2.
• Utilize Azure Data Factory components, such as linked services, datasets, pipelines, and activities, to orchestrate and automate data movement and processing workflows.
• Develop and maintain integration solutions that enable starting, pausing, and stopping Jupyter notebooks in Azure Databricks.
• Implement data loading processes to load transformed data into Azure SQL Database efficiently and accurately.
• Ensure data pipeline solutions are robust, scalable, and optimized for performance.
• Collaborate with data architects, data scientists, and other cross-functional teams to ensure data integration solutions align with business requirements and data strategies.
• Perform data validation, testing, and troubleshooting to ensure data integrity and quality throughout the pipeline.
• Monitor and optimize data pipelines to ensure efficient and reliable data movement and processing.
• Develop and maintain documentation for data pipeline solutions, including design documents, deployment instructions, and operational guidelines.
• Stay updated with the latest advancements in Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure SQL Database to continuously improve data integration capabilities.
• Provide technical guidance and support to junior team members, fostering a collaborative and learning-oriented environment.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field. Equivalent work experience may be considered.
• Proven experience as an Azure Data Engineer or similar role, with expertise in developing data pipeline solutions using Azure Data Factory.
• Strong understanding of data integration concepts and best practices.
• Experience in loading data from Network Shared Folders into Azure Data Lake Gen 2.
• Experience in initiating/running Jupyter Notebooks in Azure Databricks from Azure Data Factory
• Proficiency in SQL and experience with Azure SQL Database or other relational databases.
• Strong knowledge of Azure services, including Azure Data Factory, Azure Data Lake, and Azure SQL Database.
• Experience with data ingestion, data modeling, transformation, and loading processes.
• Strong analytical and problem-solving skills, with the ability to troubleshoot and resolve complex data integration issues.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
• Self-motivated and proactive, with the ability to prioritize tasks and manage time effectively.
• Relevant certifications as an Azure Data Engineer (DP-203), Azure Data Factory, Azure Databricks, or related technologies are highly desirable.

Method of Application

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