McDonald's - Chicago, IL
posted 2 months ago
McDonald's Global Technology - Data & Analytics team is seeking a Data Engineer with a profound understanding of the Data Product Lifecycle, Standards, and Practices. In this role, you will be responsible for constructing scalable and efficient data solutions that support the company's data products and analytics initiatives. As a Data Engineer, you will work closely with data scientists, analysts, and other cross-functional teams to ensure the availability, reliability, and performance of data systems. Your expertise in cloud computing platforms, technologies, and data engineering best practices will be pivotal in delivering high-quality data products and enabling data-driven decision-making. You will build and maintain relevant and reliable data products that align with business needs, developing and implementing new technology solutions to enhance data reliability and observability. Your participation in new software development engineering will involve defining business rules that determine data quality, assisting the product owner in writing test scripts, and performing rigorous testing to ensure data quality. A solid understanding of the technical details of data domains will be essential, as you will need to clearly understand the business problems being solved. Your responsibilities will include designing and developing data pipelines and ETL processes to extract, transform, and load data from various sources into AWS data storage solutions such as S3, Redshift, and Glue. You will implement and maintain scalable data architectures that support efficient data storage, retrieval, and processing, while collaborating with data scientists and analysts to understand data requirements and ensure data accuracy, integrity, and availability. Additionally, you will build and optimize data integration workflows, monitor and troubleshoot data pipelines, and ensure data security and compliance with governance policies. Managing data infrastructure on AWS will be part of your role, including capacity planning, cost optimization, and resource allocation. Staying updated with emerging data engineering technologies and best practices will be crucial for improving data systems and processes. You will also document data engineering processes, workflows, and solutions for knowledge sharing and future reference, and coordinate with teams distributed across time zones as needed.