Synapse Engineer

Role: Lead Synapse Engineer
Exp.: 9-12 years

Competencies

1. Proven experience as a Data Engineer, preferably with a focus on Azure Data Factory and Azure Synapse Analytics.
2. Strong understanding of data integration concepts, ETL/ELT processes, and data warehousing principles.
3. In-depth knowledge of Azure Data Factory and its various components, including pipelines, activities, data flows, and triggers.
4. Hands-on experience with Azure Synapse Analytics, including data ingestion, data transformation, and data loading techniques.
5. Proficient in SQL and scripting languages (e.g., PowerShell, Python) for data manipulation and automation tasks.
6. Familiarity with data modeling, dimensional modeling, and schema design for datawarehousing.
7. Solid understanding of cloud computing concepts and experience working in a cloud environment (preferably Azure).
8. Experience with Azure Data Lake Storage, Azure SQL Database, and other Azure data-related services.
9. Strong problem-solving skills and the ability to analyze complex data requirements and translate them into practical solutions.
10. Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
11. Azure certifications related to data engineering (e.g., Azure Data Engineer Associate) will be a plus.

Responsibilities:

1. Design, develop, and implement end-to-end data integration solutions using Azure Data Factory (ADF) and Azure Synapse Analytics.
2. Collaborate with cross-functional teams to understand data requirements, design data models, and develop data pipelines for efficient data processing and analysis.
3. Develop ETL/ELT workflows, data ingestion processes, and data transformation activities using ADF pipelines and activities.
4. Optimize data processing and storage in Azure Synapse Analytics, ensuring high performance and scalability.
5. Perform data quality checks, data validation, and data profiling to ensure data accuracy and integrity.
6. Implement data security and access controls to protect sensitive data in compliance with organizational and industry standards.
7. Monitor and troubleshoot data integration and data warehousing solutions, identifying and resolving performance issues and bottlenecks.
8. Collaborate with data architects and data scientists to design and implement data lakes, data marts, and data warehouses to support analytics and reporting requirements.
9. Stay updated with the latest Azure Data Engineering trends, best practices, and technologies, and provide recommendations for process improvements and tool enhancements.
10. Document technical specifications, data flows, and solution designs to ensure effective knowledge transfer and maintainable solutions.
11. Provide technical guidance and mentorship to junior team members, sharing your expertise in Azure Data Factory and Azure Synapse Analytics.