Apple Inc Bangalore Big Data Engineer Posts | Bachelor’s Degree/Master’s Degree | Apply Now

Apple Inc, an American multinational technology company that designs, develops, and sells consumer electronics, computer software, and online services.     

In the latest job announcement, Apple announces job vacancies for Big Data Engineer posts, with work location in Bangalore.

Under Apple Bangalore Big Data Engineer 2022 Jobs, candidates having required skills in Big Data ecosystem, Kafka, Distributed SQL Database (Snowflake, SingleStore), HBase, Cassandra can apply.

The selected candidate will be recruited with a permanent and full-time job.

An Interested and qualified candidate has to apply through online mode.

Job Designation: Big Data Engineer.

Job Code: 200440631.

Education Qualification: Bachelor’s Degree/Master’s Degree.

Experience Level: 5+ years.

Job Location: Bangalore.

Apply Mode: Online.

Key Qualifications:

• Deep experience developing large scale distributed computing systems.
• In-depth knowledge and experience in one or more of the following technologies: Big Data ecosystem, Kafka, Distributed SQL Database (Snowflake, SingleStore), HBase, Cassandra, Iceberg, Spark, Flink and Trino
• In-depth knowledge and experience in one or more of the following technologies: Big Data ecosystem, Kafka, Distributed SQL Database (Snowflake, SingleStore), HBase, Cassandra, Iceberg, Spark, Flink and Trino
• Extensive experience working with one or more SQL Database systems like PostgreSQL - define schema & DDL, maintain Stored Procedures, perform query optimizations, tracking DB metrics, and more
• Strong software development, problem-solving and debugging skills with experience in one or more of the following languages: Java, Python, Scala
• Strong software development, problem-solving and debugging skills with experience in one or more of the following languages: Java, Python, Scala
• Experience building cloud native platforms using containerization technologies like Kubernetes, docker, helm and well versed in AWS/GCP or Azure
• Ideally 5+ years of experience in crafting, implementing and supporting highly scalable data pipelines systems with high volume of data.
• Adept at quickly grasping and distilling highly complex matters into clean, understandable solutions
• Nice to have experience with data governance, security & Privacy tools like Apache Ranger, Apache Atlas
• Nice to have experience with large data reporting and data visualization tools
• Organized, detail oriented, and thorough in every undertaking
• Ability to thrive in a multi-functional team on high profile, critical projects
• Candidate should be able to initiate and explore alternate technology and approaches to solving problems.

Description:

In this role we look forward to your designing and developing software architecture for large scale data pipelines and core data storage solutions to enable analytics and ML use cases and management for the Machine Metrics system at Apple Product Operations

• You will be responsible in crafting, developing and maintaining our large-scale data pipelines, storage, and processing services
• Build self-service analytics and ML tools to help engineering teams derive actionable metrics out of large volumes of raw data
• Partner with different Ops teams, data science and engineering teams and develop platforms/apps/algorithms to answer complex questions on quality of our products.
• You will work closely with the DevOps team and develop monitoring and alerting scripts on various web, data pipelines and jobs
• You will have the opportunity to learn and work on the latest Big Data technologies, lead POCs to demonstrate new ideas and influence the future direction of our technology stack
• Review hardware infrastructure planning and provide support when required for software upgrades.

How to apply:

Interested and qualified job applicants have to apply through online mode, by initially registering with Apple career portal and login in to apply.

Apply online:

https://jobs.apple.com/en-in/details/200440631/big-data-engineer-manufacturing-systems-infrastructure?team=OPMFG