Staff Data Engineer - Experimentation

At Apple, we work every day to create products that enrich people's lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy. \\n\\nAds Experimentation team is seeking a Machine Learning Engineer and Data Engineer who will help drive innovation. This is a hands-on role for developing & supporting a state of the art ads experimentation platform. This role requires partnering with cross-functional teams to effectively coordinate the complex interdependencies inherent in application development. A successful candidate has strong technical skills and is eager to create intuitive user experiences; they have a keen eye for the details that surprise and delight our customers. While understanding our product features, you will perform rigorous analyses, measure performance and make data-driven decisions and develop scalable tools that facilitate quick and accurate decision making.

Design and build a new generation of experimentation platform for the Ads Platform organization. Apply leading-edge technologies to enable safe and data driven launch of features that help connect Apple users and advertisers while delivering on Apple's privacy commitment through experimentation. Collaborate with stakeholders and data scientists to design experiments and statistical methods that account for the marketplace dynamics and yield reliable treatment effects. \nProvide expert technical guidance to engineers and scientists on data engineering and monitoring techniques. \n\nYou will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other's growth and supporting each other in delivering for our customers and Apple.\n

8+ years of experience in software and data engineering and analysis with an in-depth understanding of SQL and spark. Industry experience in SDLC is preferred. \nAnalysis: Conduct rigorous, end-to-end analyses using SQL, Python, and statistical methods to uncover insights and improve treatment effect estimates. \nExperience with A/B testing infrastructure and methodologies and understanding of the assumptions of randomized control trials. Experience in A/B testing and/or ad tech systems is a bonus. \nProficiency in SQL and Pyspark or Scala to conduct analyses and build data products (pipelines and dashboards) to automate experiment reporting at scale. \nLead the design, development, and maintenance of scalable and reliable data pipelines. Implement robust data quality checks, monitoring systems, and data lineage tracking. Advocate best practices for data engineering. Experience with using LLMs to build scaleable data Strategic Partnership: Work directly with stakeholders, including senior leaders, to identify, scope, and prioritise high-impact questions. \nSkilled at operating in a cross-functional organization. \nAbility to understand ambiguous and complex problems and design and execute analytical approaches and turn analysis into clear and concise takeaways that drive action. \nCurious business attitude with a proven ability to seek projects with a sense of ownership. \nExcellent communication, social and presentation skills. \nDesire to work in a fast-paced and challenging work environment.\nMentor junior engineers and scientists on the team

Advanced Degree in Computer Science, Applied Math or related engineering field.\n8+ years of industry experience building scalable applications and data pipelines