SummaryPosted: Feb 17, 2025Role Number:200591769Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. We have one of the most complicated and efficient supply chains in the world, powered by world class internal systems and tools developed and managed by the Global Sourcing and Supply Management (GSSM) Solutions team. These tools enable us to effectively manage costs, supply, and bring supply chain intelligence to the forefront of our decisions. At Apple, innovative ideas quickly transform into powerful applications that drive efficiency and unlock insights for our business. By joining our Solutions team, you'll work on AI/ML-powered tools and data-driven solutions that directly support the GSSM organization, helping them streamline operations and enhance decision-making. Our team focuses on creating custom applications that tackle complex challenges, optimize workflows, and enable smarter business decisions. We build machine learning models to extract actionable insights, automate processes, and improve predictions using deep learning techniques, all aimed at making our team more efficient and effective. Are you an enthusiastic Data Engineer eager to apply your expertise in a fast-paced, innovative tech environment? Join our Global Sourcing & Supply Management (GSSM) Solutions team as a key player in revolutionizing our supply chain.DescriptionDescriptionAs Data Engineer on our core AIML team, you will be at the forefront of designing and developing scalable data systems to empower our AIML and GenAI applications. You will be working closely with business stakeholders, data scientists, and IT groups closely and take an active role in effectively communicating the recommendations to senior management. Your work will empower strategic and tactical decision-making processes within our supply chain, driving us towards greater efficiency and success. If you thrive in a collaborative environment, are passionate about leveraging AIML to solve complex business problems and are excited about the opportunity to make a significant impact in a dynamic tech industry, we want to hear from you! Key Responsibilities - Architect, develop, and test large scale data solutions, to provide efficient analytical and reporting capabilities across Apple’s supply chain teams. - Develop highly scalable data pipelines to load data from various source systems, use Apache Airflow to orchestrate, schedule and monitor the workflows. - Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear. - Ensure data quality through setting up data quality management frameworks and anomaly detection capabilities. - Communicate the results and insights effectively to partners and senior leaders, providing clear and actionable recommendationsMinimum QualificationsMinimum Qualifications5+ years of hands-on experience in data architecture, dimensional modeling, data warehousing and data engineeringProficiency in SQL, Python, and Spark, with experience handling large datasets.Experience with AIML and GenAI solutionsProficiency in design and development of custom ETL pipelines using SQL and scripting languages (Python/ Shell/ Golang) and workflow management tools like AirflowBachelor’s or Master’s degree in Computer Science, Statistics, Applied Math or a related fieldKey QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsExperience with modern data architecture like data lakes, data lakehouse and cloud computing platforms like AWS, Google CloudExperience with version control systems, CI/CD practices, testing, and migration tools for database and softwareExhibit excellent oral and written communication skills, with the ability to work individually, navigating through ambiguity or as part of a teamPassion for new and emerging technologiesAbility to communicate technical issues with a non-technical audienceManiacal attention to detailEducation & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsMore