#200519076-14
d environment where your technical abilities will be challenged on a day-to-day basis? If so, Apple's Global Business Intelligence team is looking for passionate, meticulous, technical savvy, energetic engineer who likes to think creatively. Apple's Enterprise Data warehouse team 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.
Description
Minimum Qualifications
Key Qualifications
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 a plus
Education & Experience
Bachelor's Degree or equivalent in data engineering, computer science or similar field.
Additional Requirements