Apple Ads is seeking a Data Engineering Manager to lead the design of large-scale data, analytics, and reporting systems to enable teams of analysts, business users, and data scientists by establishing standards and frameworks for reliable and efficient production of new data products, while upholding Apple's privacy commitments and transforming how advertising works with data.
Requirements
- 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
Responsibilities
- Lead a group of engineers focused on rapidly developing, scaling, and supporting data products for online and offline consumption by business and analytic stakeholders, while remaining actively engaged in technical problem-solving and solution design.
- Define and incorporate best practices in storage, processing, and copy/synchronization appropriate for the scale and maturity of our data products.
- Collaborate with business stakeholders to understand needs, align priorities, and translate them into effective data solutions.
- Work closely with cross-functional teams to prototype new concepts and deliver end-to-end systems in an agile setting.
- Produce high-quality systems with strong reliability and scalability.
- Requires a strong understanding of the intersection between business, analytics, and engineering, resulting in a proactive approach that emphasizes reusable solutions to improve efficiency and time-to-insight.
- Must be able to work in a constantly evolving environment and perform optimally in a sprint-based, agile development setting.
Other
- 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 ability to communicate technical concepts to a business-focused audience
- Passion for reinforcing and enriching an engineering team culture that drives engagement and satisfaction
- Most importantly, a sense of humor and an eagerness to learn
