Job Location: Cupertino, CA
Summary
Posted: Aug 9, 2022
Weekly Hours: 40
Role Number:200406885
Would you like to play a critical part in the next revolution of human-computer interaction? Would you like to contribute to the advancement of a product that is globally redefining how humans use voice to relate to technology? The AIML Data organization seeks to improve products (e.g Siri) by using data as the voice of our customers. Within this organization, data governance plays the critical role of ensuring consistent information design so that our data is: easy to produce, upholds privacy principles, and keeps the overall data processing architecture scalable. We’re looking for exceptional data engineers with phenomenal communication skills; who are passionate about our product and values; who love working with product and data at scale; and who are committed to the hard work required for continuous improvement. As part of this group you will be working closely with all stakeholders including product software engineers, privacy engineers, data engineers and data scientists.
Key Qualifications
- You have excellent written and verbal communication skills
- You are curious and have excellent analytical and problem solving skills
- A minimum of 4+ years of expertise working with distributed data technologies (e.g. Spark, Kafka, Hadoop, MapReduce, etc.), building efficient extraction and transformation pipelines at scale
- Proficiency in at least one high-level programming language (Java, Scala, Python, Swift, Objective-C or equivalent)
- Intimate knowledge of schema driven data products and schema evolution principles
- Experience with large, complex, highly dimensional data sets; hands-on experience with SQL
- You are pragmatic, not letting “perfect” be the enemy of “good”
- You are self-directed and capable of operating amidst ambiguity
- You are humble, continually growing in self-awareness and possess a growth mindset
Description
In this role, you will be responsible for improving the logging instrumentation architecture, governing privacy compliant schema design that manifests itself in petabytes of data volume, and strategically improving the data processing architecture that optimizes resource consumption at scale. Specifically, this opportunity will enable you to make wide ranging contributions that includes contributions to actual products, data modeling & warehousing, privacy architecture, and both batch and stream pipelines. On any given day you might be: – Defining best practices to design schemas for our most fundamental “source of truth” data such that it becomes easy to produce from the product and easy to consume in the pipeline architecture. Evaluate tradeoffs of privacy, product and data engineering realities to review the data design proposals submitted for approvals. – Influencing and contributing to improve product instrumentation architecture in iOS ecosystem. – Developing batch or streaming data pipelines and/or software libraries to process, transform, and analyze data to identify signals from the billions of events we collect every day. – Building internal services and tools to help in-house partners implement, deploy and analyze datasets with a high level of autonomy and limited friction. – Designing and implementing automated handling lifecycle of datasets (schema evolution, metadata store, backfill management, deprecation, migration). – Improving the architecture of pipelines and data warehouse to be more efficient for utilized resources.
Education & Experience
Surprise us! Many will have a Bachelor’s or Master’s in CS, Engineering, Math, Statistics, or a related field, or equivalent practical experience in engineering. 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.
Additional Requirements
- Experience of developing web or mobile applications
- Experience of instrumentation or logging libraries used by end products
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