Azure Data Engineer

You will be responsible for supporting data and analytics solutions across projects as an Azure Data Engineer with 3 to 8 years of experience. Collaborating with various projects, you will create data solutions for a variety of business use cases. Your role will involve driving innovation within Data Engineering to shape the future of data and analytics technology. As a critical team member, you will design and develop highly complex data projects, identifying gaps in the data stack and guiding advancements for the team. You will provide technical expertise in all project phases, including analysis, design, development, and implementation of cutting-edge solutions. Your input will continuously shape and improve the data environment beyond the team boundaries. Key Responsibilities: - Collaborate with various projects to create data solutions for different business use cases - Drive innovation within Data Engineering to influence the future of data and analytics technology - Design and develop highly complex data projects - Identify gaps and weaknesses in the data stack, guiding advancements for the team - Provide technical expertise in all project phases, including analysis, design, development, and implementation - Shape and improve the data environment beyond team boundaries - Understand UI needs, backend design, and data design to create backend code - Run diagnostic tests, repair defects, and provide technical support - Document Node.js processes and prepare reports - Design and implement APIs, integrating with third-party APIs as needed - Develop and maintain databases using technologies such as MongoDB or MySQL - Create reusable code and libraries for future use - Optimize applications for maximum speed and scalability - Troubleshoot and debug issues, providing timely resolutions Qualifications Required: - Excellent knowledge and experience in Azure Data Services (like ADF, etc.) along with Databricks - Good knowledge and expertise in SQL, Python, PySpark - Good understanding of ETL & Data warehousing concepts - Excellent written & spoken communication skills for interactions with customers and stakeholders - Ability to understand requirements and architecture and translate them into implementation following best practices - Self-driven with an excellent learning attitude - Experience in Snowflake Datawarehouse Good to have: - Experience & conceptual knowledge of Bigdata technologies such as Hadoop, HDFS, Hive, Spark - Knowledge and exposure to Databricks - Experience with ETL tools like Matillion, DBT, etc. - Exposure to other cloud platforms,