Data Engineer

Key Responsibilities: - Design, develop, and maintain scalable data architectures and data pipelines based on business requirements. - Perform data integration across multiple systems and platforms, ensuring alignment with company architecture standards. - Develop and manage ETL/ELT processes across various data layers within the Enterprise Data Hub. - Troubleshoot and resolve data integration issues at application, infrastructure, and network levels. - Identify bottlenecks in existing data pipelines and lead initiatives to optimize and automate processes. - Ensure data quality, reliability, and efficiency through appropriate tools and programming techniques. - Ensure data lake architecture complies with approved organizational standards and best practices. - Collaborate with cross-functional teams to support data-driven decision-making. Requirements: - Minimum 3-5 years of experience in a Data Engineer or similar role. - Strong experience in data integration and pipeline development, including cloud-based solutions. - Hands-on experience with ETL/ELT tools such as AWS Glue, Azure Data Factory, Talend, or WebMethods. - Proficient in SQL for data querying and manipulation. - Experience working with cloud data platforms such as Microsoft Azure and Amazon S3. - Strong problem-solving skills with the ability to troubleshoot complex data issues. - Experience in optimizing and automating data workflows. - Hands-on experience with MSSQL SSIS. Preferred Skills: - Experience working with enterprise-level data hubs or large-scale data platforms. - Familiarity with data governance and data architecture best practices. - Knowledge of scripting or programming languages for data processing (e.g., Python, Scala).