Software Engineer (Data Solutions), AI & Data Platforms (AiDP) at Apple

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

04 Sep, 26

Salary

0.0

Posted On

06 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Scala, Java, SQL, Snowflake, Big Query, Spark, Kafka, AWS, Azure, Google Cloud, RESTful Services, ETL, Streamlit, Tableau, Generative AI

Industry

Computers and Electronics Manufacturing

Description

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS&T) organization. IS&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless. Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here. 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. 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. This role 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 challenging 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. MINIMUM QUALIFICATIONS Knowledge of BI concepts and implementation experience on Cloud with databases like Snowflake or Big Query Programming experience in building high-quality software with at-least one of the following programming languages - Python, Scala or Java. Experience in developing highly optimized SQLs, procedures & semantic process for distributed data applications. Bachelor's degree in Computer Science or equivalent experience PREFERRED QUALIFICATIONS 3 or more years of experience building enterprise-level data applications on distributed systems Hands-on experience in designing and development of cloud-based applications that include compute services, database services, APIs to design RESTful services, ETL, queues and notification services. Experience in cloud data warehousing platforms like Snowflake is highly valued Experience developing Big Data applications using Java, Spark, Kafka is a huge plus 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: 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.

Responsibilities

Engineer scalable distributed systems on the cloud to power data exploration, analytics, and production models. Drive the development of new components from concept to release while collaborating with internal customers to streamline workflows.