Data Engineer

As a Data Engineer with 4+ years of experience in building and managing scalable data solutions, your role will involve designing, implementing, and optimizing data pipelines using Azure Data Factory. You will be responsible for implementing ETL/ELT processes for structured and unstructured data, building and optimizing data warehouses for analytics and reporting needs, and integrating data from multiple sources to ensure data quality and reliability. Working with Azure services like Data Lake, Synapse, and Databricks, you will deliver end-to-end data solutions and maintain RBAC policies for secure data access. Collaboration with data analysts, data scientists, and business stakeholders is essential to provide reliable datasets and ensure performance, scalability, and cost optimization of data pipelines. Key Responsibilities: - Design, develop, and maintain data pipelines using Azure Data Factory. - Implement ETL/ELT processes for structured and unstructured data. - Build and optimize data warehouses for analytics and reporting needs. - Integrate and manage data from multiple sources to ensure data quality, consistency, and reliability. - Work with Azure services (Data Lake, Synapse, Databricks, etc.) to deliver end-to-end data solutions. - Implement and maintain RBAC policies to ensure secure and compliant data access. - Collaborate with data analysts, data scientists, and business stakeholders to provide reliable datasets. - Monitor and troubleshoot pipelines, ensuring performance, scalability, and cost optimization. Required Skills & Qualifications: - 4+ years of experience in Data Engineering, with at least 2 end-to-end data warehouse or data lake projects. - Strong SQL expertise, including complex queries, window functions, and performance tuning. - Hands-on experience with Azure Data Services such as Azure Data Factory, Azure Databricks, Azure Data Lake, Delta Lake, Synapse Analytics, Azure Key Vault, RBAC, and security features. - Good understanding of ETL/ELT tools like Pentaho, dbt, or equivalent. - Knowledge of Big Data and distributed processing frameworks like Spark and optimization techniques. - Familiarity with version control and CI/CD for data pipelines using GitHub or Azure DevOps. - 12 years of Power BI hands-on experience. - Excellent communication, problem-solving, and leadership abilities.,