Software Engineer (Data Solutions), IS&T Ai & Data Platforms

AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning - including generative AI - along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.

At Apple, extraordinary ideas 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. Would you like to work in a fast-paced environment where your technical abilities will be challenged on a day-to-day basis? If so, Apple's Artificial Intelligence and Data Platforms (AiDP) team is seeking an experienced Software Engineer to build high quality, scalable and resilient distributed systems that power Apple's cloud analytics platforms and data pipelines. Apple's Enterprise Data Warehouse landscape caters to a wide variety of real-time, near real-time and batch analytical solutions. These solutions are an integral part of business functions like Sales, Operations, Finance, AppleCare, Marketing and Internet Services, enabling business drivers to make critical decisions. We utilize proprietary and open source technologies, Kafka, Spark, Iceberg, Airflow, Presto, etc. If you are looking to take on infrastructure problems at scale, both on-prem or in cloud, focusing on ease of use, ease of maintenance and most importantly implement solutions that are scalable, you will have fun in AiDP!

Description

We engineer high-quality, scalable and resilient distributed systems on cloud that power data exploration, analytics, reporting and production models. Our core systems are diverse and come with an unusual intersection of high data volumes with systems distributed across cloud and on-premise infrastructure.

On our team you will build solutions that integrate open source software with Apple’s internal ecosystem. You will drive development of new components and features from concept to release: design, build, test, and ship at a regular cadence. You will work closely with internal customers to understand their requirements and workflows, and propose new features and ecosystem changes to streamline their experience of using the solutions on our platform.

This is a hard-core software engineering role, where a large part of an engineer's time is spent in writing code and designing/developing applications on cloud, with the remainder being spent on tuning and debugging codebase, supporting production applications and supporting our application end users. This role requires in-depth knowledge of innovative technologies and cloud data platform with the ability to independently learn new technologies and contribute to the success of various initiatives.

We are looking for a hardworking and passionate person to join this amazing team. If you feel this is you, we'd love to hear from you

Minimum Qualifications

3 or more years experience building enterprise level applications on large-scale distributed systems with a bachelor's degree in Computer Science or equivalent experience.

Knowledge of BI concepts and implementation experience on Cloud with databases like SnowFlake or Big Query or Cloudera.

Programming experience in building high quality software. Proficiency in at-least one of the following programming languages - Python, Scala or Java.

Strong hands-on experience in designing and development of cloud-based applications that include large scale compute services, database services, APIs to design RESTful services, ETL, queues and notification services.

Experience in developing highly optimized SQLs, procedures & semantic process for distributed data applications.

Preferred Qualifications

Experience in Enterprise-ready Cloud Data-Warehousing platforms like Snowflake is highly valued.

Hands-on knowledge of Spark cluster-computing framework & Kubernetes or similar containerization technologies.

Experience developing Big Data applications using Java, Spark, Kafka is a huge plus.

Hands-on knowledge and experience in Apache Iceberg, Data Lakehouse architecture and implementation is a plus.

Experience in Apache Doris or similar real-time high concurrency analytics platform.

Understanding of fundamentals of object-oriented design, data structures, algorithm design, and problem solving.

Cloud technology experience on platforms like AWS, Microsoft Azure, Google Cloud.

Data Visualization Tools: Proficient in data visualization, with experience in software such as Streamlit, Superset, Tableau, Business Objects, and Looker.

Data Insights and KPIs: Working experience on generating and visualizing data insights, metrics, and KPIs. Usage of basic ML models in the space of anomaly detection, forecasting, GenAI.