"Responsibilities Architect and build: Design and implement scalable data architectures and pipelines on Azure, utilizing services like Azure Data Factory and Azure Synapse Analytics. Develop and optimize: Create and maintain data pipelines, including ETL/ELT processes, with a focus on performance and scalability, often using Python/PySpark and Databricks. Ensure data quality: Implement processes and checks to maintain data quality, integrity, and security across all data solutions. Collaborate: Work with data scientists, analysts, and other stakeholders to understand data needs and deliver effective solutions. Troubleshoot and monitor: Monitor data systems, troubleshoot performance issues, and ensure the smooth operation of data pipelines. Mentor and lead: Provide technical leadership and mentorship to junior data engineers. Document: Create and maintain comprehensive documentation for data workflows, processes, and best practices. Qualifications Education: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Experience: 5+ years of experience in data engineering or a similar role. Azure expertise: Proven experience with Azure data services including Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage. Databricks expertise: Advanced proficiency with Databricks, including cluster management, notebook development, and Delta Lake features. Technical skills: Strong knowledge of SQL, NoSQL databases, and big data technologies like Apache Spark (PySpark, Scala). Programming: Proficiency in programming languages like Python. Other skills: Experience with data warehousing, data modeling, and performance tuning. Excellent problem-solving and communication skills. Sr Azure Data Engineer Job Description Template - Expertia AI Responsibilities. Design and develop scalable data architectures on Azure. Implement and optimize data pipelines using Azure Data ... "