Data Engineer - Synapse Analytics (5-7 yrs)

Role : Data Engineer.

Experience : 5 to 7 years+.

Location : Remote.

Job Description :

The ideal candidate should have a strong background in working with Azure Data Factory, Azure Synapse Analytics, and Azure Analysis Services.

Knowledge of Power BI to validate and optimize the dashboards.

Responsibilities :

Data Pipeline Development: Design and implement robust data pipelines using Azure Data Factory to facilitate seamless data flow within the organization.

Data Warehousing: Utilize your expertise in Azure Synapse Analytics to build and manage scalable data warehouses, ensuring optimal performance and reliability.

Analysis Services: Develop and maintain Azure Analysis Services models for efficient data analysis and reporting, enabling stakeholders to derive valuable insights.

Data Integration: Collaborate with cross-functional teams to integrate data from various sources into our Azure-based data ecosystem.

Performance Optimization: Identify and implement performance optimization techniques to enhance the speed and efficiency of data processing and analysis.

Data Quality Management: Implement data quality checks and ensure the integrity and accuracy of data throughout the entire data lifecycle.

Monitoring and Troubleshooting: Monitor data pipelines, analyze issues, and troubleshoot any data-related problems to ensure continuous data availability.

Documentation: Maintain comprehensive documentation for data engineering processes, pipelines, and data models.

Skills :

Azure Data Factory: Demonstrated expertise in designing, developing, and managing data pipelines using Azure Data Factory, including a deep understanding of its features and capabilities.

Azure Synapse Analytics: Proven experience in building and optimizing data warehouses using Azure Synapse Analytics, with a focus on performance tuning and scalability.

Azure Analysis Services: Strong proficiency in developing and maintaining Azure Analysis Services models for effective data analysis and reporting, ensuring accessibility for business users.

SQL: Proficient in writing complex SQL queries, optimizing database performance, and ensuring data accuracy.

Data Modelling: Solid understanding of data modeling concepts and experience in designing efficient and scalable data models.

Data Integration: Experience with integrating data from diverse sources into Azure-based data ecosystems, ensuring seamless connectivity and interoperability.

Problem-Solving: Excellent problem-solving skills with the ability to identify, troubleshoot, and resolve data-related issues efficiently.

Collaboration: Ability to work collaboratively in a team environment, liaising with both technical and non-technical stakeholders to meet project objectives.

Documentation: Strong documentation skills to maintain clear and comprehensive records of data engineering processes, pipelines, and data models.

Data Quality Management: Knowledge and experience implementing data quality checks and ensuring data integrity throughout the entire data lifecycle.

Knowledge of Power BI to validate and optimize the dashboards.