Apple Hiring Cloud Data Engineer Job।Great Opportunity 2024

Apple Hiring Cloud Data Engineer Job

Job Role : Cloud Data Engineer

Salary : Rs 6,80,678 per year,

Location : Hyderabad, Telangana

Company : Apple

Qualifications : Bachelor’s degree

Experience : 4+ years

ABOUT APPLE

Cloud Data Engineer at Apple

Apple Inc., based in 1976 with the aid of Steve Jobs, Steve Wozniak, and Ronald Wayne, has evolved into one of the global’s maximum iconic generation corporations. Headquartered in Cupertino, California, Apple is renowned for its progressive merchandise such as the iPhone, iPad, Mac computers, and Apple Watch.The enterprise’s achievement is driven through its commitment to layout excellence, person experience, and cutting-edge generation integration.

Apple’s environment includes a strong App Store, iCloud offerings, and more than a few software program programs that complement its hardware services. With a focal point on sustainability and renewable electricity, Apple is actively decreasing its environmental impact. The enterprise additionally performs a vast role in international supply chain control and production, frequently putting enterprise standards.

Apple’s marketplace impact extends past consumer electronics, because it maintains to put money into regions like artificial intelligence, augmented fact, and fitness era. With a faithful customer base and a strong emblem reputation for exceptional and innovation, Apple remains a dominant pressure within the tech industry international.

Job Description

As a Cloud Data Engineer, you will design, expand, and preserve scalable facts pipelines and infrastructure on cloud platforms like AWS, Azure, or GCP. Your position entails optimizing facts retrieval and garage strategies, making sure statistics great and reliability. You’ll collaborate with statistics scientists and analysts to put into effect ETL tactics, construct statistics warehouses, and assist machine learning models. Proficiency in programming languages like Python or Scala, enjoy with SQL and NoSQL databases, and know-how of cloud services (S3, Redshift, BigQuery) are important. Strong hassle-solving capabilities and the ability to paintings in agile environments are key for success on this position.

Responsibilities for a Cloud Data Engineer: 

 

Design and Development of Data Pipelines:

  • You will be tasked with designing, building, and maintaining scalable information pipelines that ingest, transform, and cargo (ETL) records from numerous resources into facts lakes or warehouses on cloud platforms along with AWS, Azure, or GCP.
  • Implement best practices for information pipeline orchestration and automation to make certain efficiency and reliability in statistics processing workflows.

Infrastructure Management:

  • Manage cloud-based facts infrastructure, which includes garage answers (like S3, Azure Blob Storage, or Google Cloud Storage) and compute sources (using offerings like AWS EC2, Azure VMs, or Google Compute Engine).
  • Optimize infrastructure for overall performance, value-effectiveness, and scalability, leveraging cloud-local offerings and gear.

Data Quality and Governance:

  • Ensure records satisfactory and reliability during the facts lifecycle by means of imposing records validation tactics, tracking records pipelines for anomalies, and troubleshooting problems right away.
  • Implement information governance frameworks and rules to hold records integrity, safety, and compliance with regulatory requirements.

Collaboration with Data Teams:

  • Collaborate intently with records scientists, analysts, and different stakeholders to apprehend records requirements and deliver answers that help analytical and operational use instances.(Cloud Data Engineer) 
  • Support facts scientists in deploying system learning models with the aid of presenting them with get entry to to clean, dependable records units.

Performance Optimization and Monitoring:

  • Monitor system performance metrics and optimize records pipelines for performance, scalability, and fee-effectiveness.
  • Implement logging, monitoring, and alerting mechanisms to make sure well timed identity and determination of troubles impacting information pipeline performance.

Documentation and Communication:

  • Document technical designs, data flows, and operational strategies to ensure complete expertise and facilitate know-how sharing among team participants.
  • Communicate efficiently with go-useful teams and stakeholders, presenting updates on undertaking reputation, troubles, and resolutions.

Apple Hiring Cloud Data Engineer Job

Qualifications for a Cloud Data Engineer:

Technical Skills:

  • Proficiency in programming languages inclusive of Python, Java, or Scala for information manipulation, scripting, and automation.
  • Experience with SQL and NoSQL databases (e.G., PostgreSQL, MySQL, MongoDB) for facts storage, retrieval, and querying.
  • Familiarity with statistics pipeline orchestration tools including Apache Airflow, Luigi, or AWS Step Functions.

Cloud Platform Expertise:

  • Hands-on revel in with cloud offerings and platforms like AWS (e.G., S3, EC2, Redshift), Azure (e.G., Blob Storage, Azure VMs, Azure SQL Database), or Google Cloud Platform (e.G., BigQuery, Cloud Storage, Compute Engine).
  • Ability to layout and installation infrastructure the usage of Infrastructure-as-Code (IaC) equipment like Terraform or CloudFormation.

Data Engineering Skills:

  • Strong statistics of records modeling principles, information warehousing thoughts, and ETL strategies.
  • Experience in designing and optimizing facts pipelines for reliability, scalability, and standard overall performance.

Analytical and Problem-Solving Abilities:

  • Analytical mindset with the functionality to research complex facts sets and derive actionable insights.
  • Strong trouble-solving capabilities to troubleshoot issues related to records pipelines, infrastructure, and data pleasant.(Cloud Data Engineer) 

Communication and Collaboration:

  • Excellent interpersonal and communication talents to collaborate effectively with pass-practical groups and stakeholders.
  • Ability to give an explanation for technical requirements to non-technical audiences and vice versa.

Education and Certifications:

  • Bachelor’s diploma in Computer Science, Engineering, or a associated discipline. A Master’s degree or applicable certifications (e.G., AWS Certified Data Analytics – Specialty) can be extraordinary.

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