Job
Description
Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just build products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Apple's Manufacturing Systems and Infrastructure (MSI) team is responsible for capturing, consolidating and tracking all manufacturing data for Apple’s products and modules worldwide. Our tools enable teams to confidently use data to shape the next generation of product manufacturing at Apple. We seek a practitioner with experience building large-scale data platforms, analytic tools, and solutions. If you are passionate about making data easily accessible, trusted, and available across the entire business at scale, we'd love to hear from you. As a Software Engineering Manager, you are an integral part of a data-centric team driving large- scale data infrastructure and processes development, implementation, and improvement. Our organization thrives on collaborative partnerships. Join and play a key role in developing and driving the adoption of Agentic AI, LLMs, Data Mesh and data-centric micro-services. Description As an Engineering Manager, you will lead a team of engineers responsible for the development and implementation of our cloud-based data infrastructure. You will work closely with cross-functional teams to understand data requirements, design scalable solutions, and ensure the integrity and availability of our data. The ideal candidate will have a deep understanding of cloud technologies, data engineering best practices, and a proven track record of successfully delivering complex data projects. Key Responsibilities include: - Hire, develop, and retain top engineering talent - Build and nurture self-sustained, high-performing teams - Provide mentorship and technical guidance to engineers, fostering continuous learning and development - Lead the design, development, and deployment of scalable cloud-based data infrastructure and applications - Drive end-to-end execution of complex data engineering projects - Partner with Data Scientists, ML Engineers, and business stakeholders to understand data needs and translate them into scalable engineering solutions - Align technical strategy with business goals through effective communication and collaboration - Implement and enforce best practices for data security, privacy, and compliance with regulatory standards - Optimize data storage, processing, and retrieval for improved performance and cost efficiency. - Continuously evaluate and improve the system architecture and workflows - Stay current with emerging trends and technologies in cloud data engineering - Recommend and adopt tools, frameworks, and platforms that enhance productivity and reliability Minimum Qualifications Bachelor’s degree in Computer Science or a related field Minimum 8 years of experience in software development with at least 2 years in a technical leadership or management role. Proven experience as a Full stack developer, with a focus on cloud platforms. Proficient in programming languages such as Python. Strong hands-on expertise with Python frameworks (Django, Flask, or FastAPI, RESTful APIs), React.js and modern JavaScript Experience with authentication and authorization (OAuth, JWT) Strong understanding of cloud services, preferably AWS & Experience in building cloud native platforms using containerization technologies like Kubernetes, docker, helm Preferred Qualifications Knowledge of data warehouse solutions (BigQuery, Snowflake, Druid) and Big Data technologies such as Spark, Kafka, Hive, Iceberg, Trino, Flink. Experience with big data technologies (Hadoop, Spark, etc.). Experience with streaming data technologies (Kafka, Kinesis). Experience building data streaming solutions using Apache Spark / Apache Storm / Flink / Flume. Familiarity with machine learning pipelines is an added advantage. Proven ability to deliver complex, high-scale systems in a production environment. Strong people management and cross-functional collaboration skills. Submit CV
