DataLab Engineering Manager

New York City, New York, United States
Software and Services


Weekly Hours: 40
Role Number:200377297
At Apple, we work every day to build products that enrich people’s lives! Our Advertising Platforms group makes it possible for 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 Search Ads in the App Store. Our platforms are highly performant, deployed at scale, and set new standards for enabling effective advertising while protecting user privacy. The Ad Platforms Engineering team is seeking a leader to help build a robust data analysis, development, and experimentation environment. This leader will be accountable for defining and delivering a solution to empower users in all roles to use data successfully and efficiently. In this role you will work as the technical manager of a multi-functional engineering team driving the development, execution, and continuous improvement of new and existing policies, capabilities, and process. You will directly enable both our core products and our internal teams of ML Engineers, Data Scientists, analysts, and business users. You will play a meaningful role in building an environment that delivers on Apple's privacy commitments to our customers while enabling our teams to change the way advertising works with data. You will collaborate closely across our engineering, algorithms, data insights, and product organizations to deliver relevant data and capabilities to inform our strategy and decisions. A successful candidate will have previous experience leading teams of engineers and architects and designing cloud based data exploration and processing systems. They will have experience with Amazon Web Services, Microsoft Azure, Google Cloud Platform, or similar. Additionally a keen understanding of data storage and processing technologies such as Spark, Kafka, EMR, Hadoop, EKS, Snowflake, Redshift, and similar.

Key Qualifications

  • Experience designing and building ad hoc and managed data science and analytics environments using various (Spark, Hadoop, Kafka, Snowflake, Vertica) distributed technologies
  • Experience with platform approaches to data architecture at scale and supporting data science teams
  • You understand modern data architectures, stay on top of developments, and are aware of what other leading players are doing
  • The ability to manage, cultivate, and grow teams of engineers and analysts
  • Experience with and ability to design for multiple cloud environments including Amazon Web Services, Microsoft Azure, Google Cloud Platform, or similar.
  • Experience with DataBricks, Jupyter, SageMaker or equivalent tool stacks
  • You take a value-driven approach to data management, seeking to enable the productive use of data while delivering on our privacy commitments
  • Snowflake, SparkSQL, Hive, Athena, Druid, Presto, Cassandra, or other Big Data query engine experience a plus
  • Advanced skills using one or more scripting languages (e.g., Python, bash, etc.) a plus
  • Experience with applying data encryption and data security standards
  • A passion to reinforce and enrich an engineering team environment, driving team engagement and satisfaction and most meaningfully, a sense of humor and an eagerness to learn


At Ad Platforms, we are constantly building and deploying new products designed to provide amazing user experiences for our customers and drive value for publishers and developers. We are looking for a data lab Engineering Manager to guide the evolution of our data capabilities to meet the challenges of increasing scale and complexity in what we deliver. Lead the design and instantiation of a privacy first data lab capability to enable online and offline creation and consumption of data by various partners. Define and institute standard methodologies in data storage, governance, processing, copy/synchronization, lifecycle management, etc. appropriate to the scale and maturity of our products. Work with multi-functional teams to prototype new architectures and concepts to deliver end-to-end systems in an agile setting. Produce high quality processes that lead to the productive use of data systems with excellent reliability and scalability. Requires a strong understanding of the intersection between business and engineering resulting in a proactive approach, focusing on reusable solutions, to improve efficiency and time to insight.

Education & Experience

Background in computer science, mathematics, or similar quantitative field with a minimum of 8 years professional experience

Additional Requirements

  • Location options: NYC, Austin