{"id":3432401,"url":"https://alion.io/job/apple-data-engineer-apple-ads-4","title":"Data Engineer, Apple Ads","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"A","score":91,"open_postings":867,"ghost_share":0,"stale_share":0.161,"repost_share":0.002,"time_to_fill_p50_days":97,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":127000,"max_usd":270000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":376},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Informatica","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"SSIS","optional":false},{"name":"Talend","optional":false},{"name":"Amazon EKS","optional":true},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Flink","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-28T22:18:08Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-30T16:58:01Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses.\nOur technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone.\nrmant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy.\nDescription\nThe Ad Platforms Data team is seeking a Data Engineer specializing in building high performance data stores to enable next generation analytical solutions. In this role, you will work as a key member of a data-centric team to drive the development, execution, and continuous improvement of core data infrastructure and processes. You will have a key role in the joint design and development of the data model, pipelines, implementation and delivery of the analytical data warehouse supporting our suite of customer experiences in addition to ad hoc and advanced analytics.\nYou will be a key enabler for teams of architects, engineers, analysts, data scientists, and business users. A successful candidate will have experience building data processing pipelines, data models and managing cloud based data warehouse platforms.\nMinimum Qualifications\nMinimum 1+ years experience in Cloud Data Engineering, preferably with a background in computer science, mathematics, or a related quantitative field.\nExpertise in building Cloud Data Warehouses in Snowflake, Redshift, BigQuery or analogous architectures.\nDeep SQL expertise, data modeling, dimensional modeling and experience with data governance\nExperience with the practical application of data warehousing concepts, methodologies, and frameworks\nExperience using data processing tools and technologies such as Python, Spark, Talend, Informatica, SSIS or DBT\nEmbrace data platform thinking, design and develop data pipelines keeping security, scale, uptime and reliability in mind\nAble to confidently express the benefits and constraints of technology solutions to technology partners, stakeholders, and team members.\nBachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.\nPreferred Qualifications\nExperience designing and operating petabyte-scale data processing systems.\nDeep expertise in Apache Spark performance tuning and optimization.\nExperience with both batch and real-time/streaming architectures, including Kafka and/or Flink.\nExperience building data platforms or processing frameworks that are reused by multiple teams or pipelines.\nExperience with AWS technologies, including S3 and Kubernetes/EKS or equivalent cloud 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