Data Engineer Snowflake | Azure | Power BI

As a Data Engineer specializing in Snowflake, Azure, and Power BI, your role will involve designing, developing, and maintaining scalable data platforms, ETL/ELT pipelines, enterprise data warehouses, and business intelligence solutions to support reporting and analytics initiatives across the organization. You must have hands-on experience with various Azure services, Snowflake, Python, PySpark, SQL, and Power BI. Your expertise in modern cloud-based data architectures and data engineering best practices will be crucial for success in this role. Key Responsibilities: - Design, develop, and maintain scalable data pipelines and data integration solutions. - Build and optimize ETL/ELT processes using Azure Data Factory, Azure Databricks, and Snowflake. - Develop and manage enterprise data warehouses and dimensional data models. - Design efficient data models using Star Schema and Dimensional Modeling techniques. - Create and maintain interactive dashboards, reports, and KPIs using Power BI. - Develop scalable data transformation and processing solutions using Python, PySpark, and SQL. - Build and maintain data lakes using Azure Data Lake Storage (ADLS). - Implement data solutions using Azure Synapse Analytics and Azure SQL Database. - Develop Azure Function Apps for data processing, automation, and integration requirements. - Work with Kafka for real-time data ingestion and event-driven data processing. - Manage structured and semi-structured data using MongoDB and other NoSQL technologies. - Collaborate with business stakeholders, analysts, and engineering teams to translate business requirements into technical solutions. - Implement CI/CD pipelines using GitHub Actions for automated deployments and platform management. - Ensure data quality, governance, security, reliability, and performance across enterprise data platforms. - Troubleshoot and optimize data workflows, pipelines, and reporting solutions. Required Skills & Qualifications: Data Engineering: - 56 years of experience in Data Engineering and Data Platform development. - Strong expertise in Data Warehousing concepts and best practices. - Experience with Data Modeling and Dimensional Modeling techniques. - Strong understanding of scalable data architecture and design patterns. Cloud & Data Platforms: - Hands-on experience with Snowflake, Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), Azure SQL Database, and Azure Synapse Analytics. Programming & Data Processing: - Strong proficiency in Python, PySpark, and SQL. - Experience building scalable ETL/ELT and data transformation pipelines. - Experience developing Azure Function Apps. Business Intelligence: - Strong expertise in Power BI. - Experience creating dashboards, reports, KPIs, and visualizations. - Understanding of report optimization, performance tuning, and data storytelling. Data Integration & Streaming: - Experience with Kafka and event-driven architectures. - Experience integrating data from multiple enterprise systems. Databases: - Strong experience with SQL databases. - Experience with MongoDB and NoSQL technologies. DevOps & Automation: - Experience implementing CI/CD pipelines using GitHub Actions. - Understanding of deployment automation and DevOps practices for data platforms. Preferred Qualifications: - Experience with large-scale cloud migration projects. - Knowledge of Data Governance and Data Quality frameworks. - Experience working in Agile/Scrum environments. - Familiarity with Microsoft Power Platform and Power Apps. - Exposure to real-time analytics and streaming architectures. Professional Skills: - Strong analytical and problem-solving abilities. - Excellent communication and stakeholder management skills. - Ability to work collaboratively within cross-functional teams. - Strong attention to detail and commitment to delivering high-quality solutions. Education: Bachelors degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. The above description outlines the responsibilities, qualifications, and skills required for the role of Data Engineer specializing in Snowflake, Azure, and Power BI. As a Data Engineer specializing in Snowflake, Azure, and Power BI, your role will involve designing, developing, and maintaining scalable data platforms, ETL/ELT pipelines, enterprise data warehouses, and business intelligence solutions to support reporting and analytics initiatives across the organization. You must have hands-on experience with various Azure services, Snowflake, Python, PySpark, SQL, and Power BI. Your expertise in modern cloud-based data architectures and data engineering best practices will be crucial for success in this role. Key Responsibilities: - Design, develop, and maintain scalable data pipelines and data integration solutions. - Build and optimize ETL/ELT processes using Azure Data Factory, Azure Databricks, and Snowflake. - Develop and manage enterprise data warehouses and di