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Apple

engineering opportunity

Staff Data Engineer

You will lead the data engineering and architecture for a centralized security data platform to manage risk and vulnerability findings. This involves owning data models, building production-grade pipelines, and creating services for ownership attribution and risk enrichment.

Austin, Texas, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at Apple?

We are the Risk and Vulnerability Management (RVM) team in Apple Services

Engineering (ASE) Security. We manage security risk for the infrastructure,

platforms, and services behind iCloud, App Store, Apple Music, TV+, and

Commerce. Findings reach us from scanners, red team engagements, design reviews,

vendor advisories, threat intelligence, and bug bounty. Our job is to turn all

of that into one prioritized backlog engineering teams can work from, and a

posture picture leadership can trust. Most of that job is data work. Signal

arrives from dozens of systems at different quality and age, and it rarely says

which asset, which service, or who owns it, so someone pieces that together by

hand before anyone can act on it. That manual step sets the ceiling on how fast

we identify and triage risk, and on how fast our partners can fix it. We are

consolidating this onto one security data platform: a system of record for

findings, a graph for ownership and blast radius, and a lakehouse for posture

metrics and analytics.

DESCRIPTION

We are looking for a Staff Data Engineer to lead the data engineering and data

architecture behind it. You will own the data model and the pipeline contracts

other teams build against, move pipelines from prototype into production the

business depends on, and make ownership attribution and risk enrichment a

service instead of repeated one-off work. Success here takes deep distributed

data engineering experience, real data judgment, and the ability to hold a

technical direction across a large, matrixed engineering organization.

MINIMUM QUALIFICATIONS

15+ years of experience working with Spark and other distributed data

technologies (e.g. Hadoop, Presto, Flink, Druid) for building efficient & large

scale data pipelines Highly proficient in at least one of Java, Python or Scala

Deep expertise in Data Principles, Data Architecture & Data Modeling, Strong SQL

skills Strong problem solver with meticulous attention to detail, capable of

taking on loosely defined problems Experience working in a complex, matrixed

organization involving cross-functional, and/or cross-business projects Strong

communication and collaboration skills & ability to lead high-level discussions

on technology strategy and approach Conceptually familiar with AWS cloud

resources (S3, EC2, RDS etc) Conceptually familiar with OSI model and

understanding of how network works (Load Balancer, Routers, network tagging,

NetFlow) Conceptually familiar of the full technology stack (from BMCs,

Firmware, to OS layer, to containers and applications) primitives

PREFERRED QUALIFICATIONS

Experience with Cloud Computing platforms like Amazon AWS, Google Cloud

Experience with building stream-processing applications using Apache Flink,

Spark-Streaming, Apache Storm, Kafka Streams or others Experience with Search

systems (such as ElasticSearch, Solr), NoSQL datastores (such as HBase,

Cassandra, MongoDB) Experience building distributed, high-volume data services

is a plus

Which skills does this role require?

JavaPythonScalaData ArchitectureData ModelingSQLDistributed SystemsHadoopPrestoDruidData EngineeringSecurity Risk ManagementS3EC2RDSOSI ModelNetwork TaggingNetFlowSecurityRisk ManagementVulnerability ManagementGCPPrototyping

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