| Data Analytics | ||
|---|---|---|---|
| Advanced (6-9 years experience) | ||
| (No Value) | ||
| Location specific role to Cupertino, CA; Data Product Manager (DPM) / Data Engineer Hybrid ABOUT THE ROLE We are looking for a Data Product Manager who can operate well beyond writing instrumentation specifications. This is a broad, strategic role that bridges business, analytics, and engineering. You will drive the strategy, design, and delivery of next-generation analytical data products, partnering with stakeholders across multiple lines of business to define the right metrics, semantic layers, and visualizations that leadership relies on to make decisions. RESPONSIBILITIES " Own the strategy, design, and end-to-end delivery of analytical data products and visualizations " Bridge business, analytics, and engineering teams, translating business needs into well-defined instrumentation, metrics, and data models " Define and standardize metrics and semantic layers across multiple lines of business " Engage executive and cross-functional stakeholders, communicating effectively with both technical and non-technical audiences " Partner with engineering on data pipeline design, modeling, and delivery workflows MINIMUM QUALIFICATIONS " 8+ years of experience designing, developing, and deploying next-generation analytical data products " 3+ years as a Senior IC leading the development of data products and visualizations across multiple lines of business " Proficiency in SQL and Scala with hands-on experience in data pipeline tools (Apache Spark, Kafka, Airflow), CI/CD practices, and version control " Strong understanding of data warehousing, data modeling (dimensional/star schemas), and metric standardization " Strong hands-on experience in SQL, Spark, and Scala and data pipeline tools " Excellent executive communication skills with both technical and non-technical audiences PREFERRED QUALIFICATIONS " Strong hands-on experience with SQL, Spark, and Scala in a production environment " Experience building and maintaining large-scale data pipelines with a focus on scalability, performance, reliability, and data quality " Experience with modern data platforms and lakehouse technologies (Iceberg, Trino, Superset) " Good understanding of data modeling, analytics, and metric design " Good problem-solving skills with ability to investigate complex data issues and derive actionable insights " Exposure to AI/ML, recommendation systems, feature engineering, GenAI, RAG, or other AI-powered data products (role is not exclusively AI-focused) |
| Location | Austin, TX |
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