Senior Data Engineer

The Senior Data Engineer will own the evaluation, enhancement, and management of enterprise data platforms, partnering with cross-functional teams to implement innovative cloud-based solutions, ensure data quality, and optimize system performance. This role will shape data governance standards and support advanced analytics, empowering organizational decision-making and operational efficiency., * Manage, evaluate, and optimize existing finance-related data platforms, leveraging emerging technologies, cloud services, and best practices to improve scalability, security, and data accessibility.

• Lead efforts to modernize data infrastructure, including migrating data to cloud platforms such as Snowflake, Microsoft Fabric, or similar, ensuring robust data processing capabilities.
• Develop, implement, and maintain standards and procedures for data governance, data integration, quality assurance, and lifecycle management to ensure data consistency, accuracy, and timeliness across data assets.
• Design, build, and support scalable ETL/ELT pipelines and data models that support data warehousing, reporting, and analytics initiatives.
• Collaborate with IT, Business Units, and senior management to align data strategies, foster a data-driven culture, and support organizational goals.
• Monitor, troubleshoot, and optimize data systems and workflows, identifying opportunities for process improvements and system performance enhancements.
• Integrate structured and semi-structured data formats such as JSON and XML, and work with APIs for seamless data ingestion.
• Automate workflows using Python and manage source control with Git or similar tools to ensure reliable and repeatable data processes.
• Maintain a strong understanding of relational databases, data management systems, and performance tuning best practices.
• Stay informed on AI and large language model technologies to explore potential data application integrations.

• Bachelor's degree in Computer Science, Data Science, or related field preferred.
• Minimum of five years of experience in senior data engineering, database architecture, or data platform management.
• Proven expertise designing and maintaining data pipelines, data warehouses, and analytical models.
• Advanced SQL development, data modeling, and performance tuning skills.
• Experience working with cloud-based data platforms and services, such as Snowflake, Microsoft Fabric, or similar.
• Proficiency in Python scripting for automation and data processing tasks.
• Familiarity with API integration, JSON, XML, and other structured/semi-structured data formats.
• Experience with version control systems such as Git.
• Strong understanding of data governance, security, and lifecycle management.
• Experience working within Agile development frameworks.