Apple-posted 3 months ago
Manager
New York, NY
5,001-10,000 employees

At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group enables people around the world to easily access informative and imaginative content on their devices, while helping publishers and developers promote and monetize their work. Our technology and services power advertising in Apple News and in Search Ads on the App Store. These platforms are highly performant, deployed at scale, and set new standards for delivering effective advertising while protecting user privacy. The Apple Ads data team is seeking a hands-on Data Engineering Manager to lead the design of large-scale data, analytics, and reporting systems. In this role, you will serve as both a technical contributor and a people leader, guiding a product-focused data engineering team while driving the development, execution, and continuous improvement of new and existing capabilities. You will directly enable teams of analysts, business users, and data scientists by establishing standards and frameworks that ensure the reliable and efficient production of new data products. You and your team will play a crucial role in building data products that uphold Apple’s privacy commitments and transform how advertising works with data. You will collaborate closely with cross-functional teams to deliver actionable data insights that drive business strategies and decisions.

  • Guide the evolution of data products to meet challenges of increasing scale and complexity.
  • Lead the team in delivering high-quality systems while engaging in technical problem-solving and design.
  • Establish standards and frameworks for reliable and efficient production of new data products.
  • Collaborate with cross-functional teams to deliver actionable data insights.
  • 3+ years of experience managing teams of software engineers and analysts.
  • Solid background in computer science, mathematics, or similar quantitative fields with a minimum of 8 years of professional experience.
  • Demonstrated expertise in practical applications of data warehousing concepts, methodologies, and frameworks using various distributed technologies such as SparkSQL, PySpark, Java, Scala, Hadoop, Kafka, Snowflake, and Vertica.
  • Proven ability to design for multiple cloud environments including Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
  • Hands-on experience with SparkSQL, Hive, Druid, Cassandra, Solr, or other big data query engines.
  • Deep understanding of modern data architectures at scale, especially serving data as a platform in support of data science teams.
  • Advanced skills using one or more scripting languages (e.g., Python, Bash).
  • Proficiency in applying data encryption and data security standards.
  • Expertise in modern table formats such as Apache Iceberg and file formats such as Parquet.
  • Knowledge of visualization tools such as Tableau and ThoughtSpot.
  • Demonstrated ability to communicate technical concepts to a business-focused audience.
  • Passion for reinforcing and enriching an engineering team culture that drives engagement and satisfaction.
  • A sense of humor and an eagerness to learn.
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