Senior Data Engineer at EVERSANA1

We are seeking an experienced and skilled  ETL Developer/ Data Engineer with a strong background in Data Warehouse, Data Vault and Snowflake Cloud technologies. The candidate must possess deep understanding of ETL architecture and best practices, coupled with the ability to design, develop, and maintain robust ETL solutions for our data-driven organization. As an ETL Developer/ Data Engineer, you will play a critical role in building and optimizing our data integration processes to support business analytics and decision-making. Skills: • Mandatory: Snowflake, dbt, Fivetran, sql. • Good to have : Python for data analytics.Responsibilities: •            ETL Architecture and Design: Designing and implementing ETL & CDC solutions, considering scalability, maintainability, and performance. Collaborating with data architects and stakeholders to define ETL specifications and data integration requirements. •            Data Warehouse and Data Vault Development: Building and managing data warehouses and data vaults to ensure efficient data storage and retrieval. Employing best practices for data modeling, schema design, and data lineage. •            Snowflake Cloud Expertise: Demonstrating expertise in Snowflake Cloud data warehousing platform. Utilizing Snowflake's features and capabilities to optimize ETL performance and data processing. •            ETL Development: Developing, testing, and maintaining ETL workflows, data pipelines, and data transformations using ETL tools like DBT, Qlik compose etc. •            Performance Optimization: Identifying and resolving performance bottlenecks in ETL processes to ensure data processing efficiency and reduce load times. •            Data Quality and Validation: Implementing data quality checks, validation, and error handling within ETL processes to ensure data accuracy and consistency. •            Documentation and Best Practices: Creating detailed technical documentation, including data mappings, ETL specifications, and system architecture. Promoting and adhering to ETL best practices and standards. •            Collaboration and Teamwork: Collaborating with cross-functional teams, including data engineers, data analysts, and business stakeholders, to understand data requirements and deliver high-quality data solutions. •            Troubleshooting and Support: Investigating and resolving ETL-related issues, providing technical support, and participating in on-call rotations if required. •            Continuous Learning and Innovation: Staying up-to-date with the latest trends and advancements in ETL technologies, data warehousing, and cloud-based data solutions. Identifying opportunities for process improvement and innovation.