Location
Seattle, WA | United States
Job description
Apple Capacity Engineering team within Apple Services Engineering org is focused on engineering driven approach to build a centralized data lake to enable products and automation to manage capacity, forecast, attribute, measure, report and optimize Apple cloud infrastructure. This will include crafting systems to model, ingest, process and compute large-scale, infrastructure data across multi cloud domain.
We collaborate with cross-functional and engineering teams across Apple to build large-scale data pipelines, to drive both description and predictive analysis, as well as visualize the data via various tools, frameworks, and services. This is your opportunity to help engineer highly visible global-scale systems with petabytes of data, supporting hundreds users. Come join us to help deliver the next amazing Apple product!
Key Qualifications
- 5+ years of experience in data engineering, with demonstrated capability in distributed computing technologies (e.g. Spark), ETL, query performance optimization, and modern SDLC methods (e.g., CI/CD, {unit, integration, e2e} testing)
- Mastery of at least one general-purpose programming language, and SQL proficiency * Passion for building and improving data pipelines that are performant, easy to maintain, and consistently deliver high-quality data products
- Proficiency in various data modeling techniques, such as ER, Hierarchical, Relational, Dimensional or NoSQL modeling.
- Experience working in a cloud infrastructure environment and using various AWS/GCP technologies
- 2+ years experience with orchestration tools such as Airflow, Control-m, Azure data factory, AWS Step function etc.
- Exposure to container services such as dockers and Kubernetes
- Some exposure/experience with data visualization tools such as Tableau, QuickSight, QlickView, IBM Cognos analytics or Business Objects
Description
You will complement several experienced data engineers forming a team with the responsibility of enabling better decision making across Apple to help optimize Apple cloud infrastructure.
In this role, you will be collaborating with data scientists, software engineers, data engineers, program managers, leadership and cross-functional team to understand requirements and translate them into scalable, reliable, and efficient data pipelines, data processing workflows and produce "data" as a product which enable "ease of use".
You will be responsible for architecting and implementing large scale systems and data pipelines with a focus on agility, interoperability, simplicity, and reusability. You should have deep knowledge in infrastructure, warehousing, data platform, data protection, security, data collection, processing, data modeling, and metadata management, and able to build an end-to-end solutions that also support metadata logging, anomaly detection, data cleaning, transformation, etc.
The ideal candidate is a highly motivated, collaborative, and proactive individual who can communicate effectively and can adapt and learn quickly.
Education & Experience
Bachelors degree or equivalent experience in Computer Science, Information systems, Software Engineering, Data Science or related field. Advanced degree in a related field a plus.
Additional Requirements
Pay & Benefits
- At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $131,500.00 and $198,100.00, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
You will complement several experienced data engineers forming a team with the responsibility of enabling better decision making across Apple to help optimize Apple cloud infrastructure.
In this role, you will be collaborating with data scientists, software engineers, data engineers, program managers, leadership and cross-functional team to understand requirements and translate them into scalable, reliable, and efficient data pipelines, data processing workflows and produce "data" as a product which enable "ease of use".
You will be responsible for architecting and implementing large scale systems and data pipelines with a focus on agility, interoperability, simplicity, and reusability. You should have deep knowledge in infrastructure, warehousing, data platform, data protection, security, data collection, processing, data modeling, and metadata management, and able to build an end-to-end solutions that also support metadata logging, anomaly detection, data cleaning, transformation, etc.
The ideal candidate is a highly motivated, collaborative, and proactive individual who can communicate effectively and can adapt and learn quickly. Bachelors degree or equivalent experience in Computer Science, Information systems, Software Engineering, Data Science or related field. Advanced degree in a related field a plus.
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