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Cloud Data Engineer
AppleHyderabad, Telangana, India4+ years
Apply 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. Imagine what you could do here.
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. The Enterprise Data warehouse team within AiDP deals with Petabytes of data catering to a wide variety of real- time, near real-time and batch analytical solutions. These solutions are integral part of business functions like Retail, Sales, Operations, Finance, AppleCare, Marketing and Internet Services, enabling business drivers to make critical decisions. We use a diverse technology stack such as Snowflake, Spark, HANA, SingleStore, Kafka, Iceberg, Cassandra and beyond. Designing, developing and scaling these big data solutions are a core part of our daily job!
As a Cloud Data Engineer you will design, develop and implement modern cloud based data warehouse/ data lakes and influence overall data strategy for the organization
- Translate complex business requirements into scalable technical solutions meeting data warehousing/analytics design standards.
- Strong understanding of analytics needs and proactive-ness to build solutions to improve the efficiency along with that help implement leading data practices & standards.
- Collaborate with multiple multi-functional teams and work on solutions which has larger impact on Apple business.
- Ability to communicate effectively, both written and verbal, with technical and non- technical multi-functional teams.
- You will get along with many other internal/external teams to deliver elite products in an exciting rapidly changing environment.
- Ability to manage partner communication & project risks.
- Thrives in a multifaceted environment, maintaining composure and a positive attitude.
- 4+ years of Hands on Experience in developing and building data pipelines on Cloud & Hybrid infrastructure for analytical needs.
- Experience working with cloud based data warehouse solutions - Snowflake, SingleStore etc., along with expertise in SQL and Advance SQL.
- High expertise in modern cloud warehouse, data lakes and implementation experience on any of the cloud platforms like AWS/GCP/Azure - preferably AWS.
- Experience working with data at scale (peta bytes) with big data tech stack and advanced programming languages e:g Python, Scala.
- Experience in designing and building dimensional data models to improve accessibility, efficiency and quality of data.
- Database development experience with Relational or MPP/distributed systems such as Snowflake, SingleStore.
- Dedicated, highly motivated with learnability skills
- Excellent problem solving, critical thinking with ability to evaluate and apply new technologies in a short time
- Strong written and oral communication skills
- Experience in working with global collaborators with ability to influence decision making.
- Exposure working in Data Science projects will be nice to have
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