Senior Data Engineer - Jobs - Careers at Apple
- Build and run Spark streaming and batch pipelines in Scala or Java, including backfills when data issues are found or new transformations are added for past events
- Design lakehouse tables and layouts (partitioning, sort order, compaction, schema evolution) so dashboards can query Iceberg quickly through Trino
- Validate incoming events, handle schema changes, and route malformed or unknown events to a dead-letter path for review and replay
- Define and enforce data quality with a data analyst: keep schemas and data contracts under version control with compatibility checks in CI, monitor freshness, completeness, duplicates, and late arrivals, and alert the right owner
- Partner with the full-stack engineer who builds the dashboards, designing the tables and queries behind them and using AI coding tools to move faster while checking the results
- Take over the Apache Flink job that ingests events from Kafka into Iceberg
- Improve performance and cost by right-sizing jobs, fixing skew and small-file problems, and tuning queries and storage
- Join the on-call rotation for Data Lakehouse incidents, review code and designs, and mentor other engineers
- Bachelor's degree in Computer Science, Engineering, or a related field
- 7+ years of professional data engineering experience building production data pipelines at scale, including diagnosing and improving the performance of data jobs and queries, or equivalent advanced degree plus experience
- Production experience with Apache Spark, including batch and streaming (Structured Streaming) pipelines
- Strong data modeling skills, with experience designing analytics schemas on Apache Iceberg or comparable lakehouse table formats
- Proficiency in Java or Scala, and strong SQL
- Experience building data quality checks and monitoring for production pipelines, including freshness and completeness alerting and reconciliation between source and derived data
- Productive use of AI coding tools in real delivery, with the discipline to validate generated code and queries
- Excellent communication and critical thinking skills in a team environment
- Production experience with Apache Kafka as a streaming source
- Production experience with Apache Flink, including the Iceberg sink, exactly-once delivery, and stateful jobs on Kubernetes
- Experience with data contracts and schema management as code (for example schema registries or dbt model contracts)
- Experience tuning tables and queries for a distributed SQL engine such as Trino
- Experience with workflow orchestration and Python automation
- Experience building dashboards or data applications that put data in front of users, with attention to visual design
- Experience owning the design of a data platform or pipeline, not just implementing it
- Experience mentoring engineers and leading cost or reliability improvements
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🇬🇧 English