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Apple AIML - Data Engineer, Data and ML Innovation in Cupertino, California

AIML - Data Engineer, Data and ML Innovation

Cupertino,California,United States

Machine Learning and AI

The AIML Data organization seeks to improve products by using data as the voice of our customers. Within this organization, the Siri Data Engineering team builds systems that process data reliably at scale to generate scalable and high-quality datasets that support confident, data informed decision-making for Siri to be an effective product. We’re looking for exceptional data engineers who are passionate about our product and values; who love working with data at scale, and who are committed to continuously improve. As a part of this group, you will work with petabytes of data daily using diverse technologies. You will be expected to effectively partner with upstream engineering teams and downstream consumers, including data scientists and ML engineers.

Key Qualifications

  • 7+ years of technical experience designing, building, and maintaining distributed data processing platforms.

  • 5+ years of industry experience working with batch or streaming distributed data processing technologies (e.g. Hadoop, MapReduce, Spark, Flink, Kafka, Presto, etc.) for building efficient & large-scale data pipelines.

  • 3+ years of data modeling experience designing data warehouse table schemas and logging schemas.

  • Proficiency in at least one high-level programming language (Java, Scala, Python, Go or equivalent).

  • Experience with large, complex, highly dimensional data sets; hands-on experience with SQL.

  • Experience working with cross-functional teams to collect business requirements, build consensus, and manage expectations.

  • You are self-directed and capable of operating amidst ambiguity.

  • You are humble, continually growing in self-awareness, and possessing a growth mindset.

  • You are curious and have excellent written and verbal communication as well as problem-solving skills.

  • You are excited about digging into massive petabyte-scale semi-structured datasets.

Description

In this role, you will be building ultra large scale batch & streaming datasets to support analytics, experimentation and machine learning and helping to drive our self-serve strategy for reporting on-behalf of data scientists and product engineers as we collectively make product better. You will help design instrumentation required to log data from device and server side and validate data is flowing in the correct shape, frequency, and quality into the Data Warehouse. Curate a high performance and easy to understand data model that meets the needs of the many. Identify common patterns and build self-serve tools to scale data engineering, and automate lifecycle of datasets with highest standards of data quality. Educate your consumers on how to access your products, assuring transparency and understanding in logic definitions and enabling self-service.

Education & Experience

Surprise us! Many will have an MS or BS in CS, Engineering, Math, Statistics, or a related field or equivalent practical experience in data engineering.

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 $138,900.00 and $256,500.00, 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 (https://www.apple.com/careers/us/benefits.html) 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.

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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. Learn more about your EEO rights as an applicant (Opens in a new window) .

Apple will not discriminate or retaliate against applicants who inquire about,disclose,or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco,review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area.

Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

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