AIML - Sr Software Data Engineer, Evaluation
Apple
Full-time
On-site
Seattle, Washington, United States
Data Science & Analytics
In this role, you’ll work cross-functionally across product and data science teams to build large-scale stream and batch processing data pipelines that power Analytics, Experimentation, and Machine Learning. You will design a unified and groundbreaking data processing framework using Flink, and/or Spark. Your work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the framework’s capabilities to new user scenarios and groundbreaking machine learning applications. You will collaborate closely with Siri, Search, and other teams to design solutions that transform raw data into datasets that drive innovation. You’ll automate dataset lifecycles with strong quality standards and help partners confidently use the data for product insights.
- 7+ years of experience designing, building, and maintaining distributed data processing systems at scale.
- 5+ years of hands-on experience with stream and/or batch processing technologies such as Flink, Spark, Kafka, Airflow, Iceberg, and Trino.
- Strong in algorithms, data structures, data modeling, and SQL, with experience working on large-scale, complex, and high-dimensional datasets.
- Proficient in at least one modern programming language (e.g., Java, Scala, and Python).
- MS or BS in Computer Science, Engineering, Math, Statistics, or a related field, or equivalent practical experience in data engineering.
- Experience with machine learning algorithms or pipelines, particularly in the context of data engineering.
- Experience supporting ML engineers or data scientists with feature engineering or model data pipelines is a plus.
- Familiarity with testing tools and methodologies for validating large-scale, distributed data systems (e.g., data quality checks, pipeline testing frameworks, fault tolerance testing).
- Proven software engineering fundamentals, including experience with design, testing, version control, and CI/CD best practices.
- Comfortable working independently in a fast-paced, ambiguous environment.
- Excellent communication and problem-solving skills.