Senior Product Analytics Engineer

Renesas ElectronicsLa Jolla, CA

About The Position

We are looking for a highly technical Senior Analytics Engineer to own and evolve our end-to-end product analytics platform. This role is responsible for the complete analytics data lifecycle — starting with analytics instrumentation embedded in product source code, through event collection and ingestion, raw data storage, transformation and aggregation pipelines, and ultimately the presentation of trusted analytics through dashboards, reports, and analytical tools. The successful candidate will act as the owner of the analytics flow, ensuring that analytics data is accurate, reliable, scalable, well-defined, and usable across the organization. This is not primarily a dashboard-building or reporting role. It is an engineering-focused position responsible for the architecture, implementation, operation, and continuous improvement of the analytics platform.

Requirements

  • Strong software engineering and data engineering background.
  • Hands-on experience building and operating production analytics or data platforms.
  • Advanced SQL skills.
  • Experience designing ETL/ELT and data transformation pipelines.
  • Experience with event-based product analytics.
  • Understanding of analytics instrumentation within web applications, backend services, and distributed systems.
  • Experience working with data lakes, data warehouses, or lakehouse architectures.
  • Experience designing analytical data models and aggregation pipelines.
  • Experience with BI and analytics visualization platforms.
  • Strong understanding of data quality, lineage, observability, and governance.
  • Ability to troubleshoot data issues across multiple layers — from application source code to the final dashboard.
  • Ability to work directly with software engineers and review or contribute to analytics-related application code.
  • Experience with multi-tenant product analytics.

Responsibilities

  • End-to-End Analytics Platform Ownership
  • Product Analytics Instrumentation
  • Data Collection and Raw Data Layer
  • Data Pipelines, Importers, and Processing
  • Analytics Data Models and Metrics
  • Analytics Presentation Layer
  • Data Quality and Observability
  • Analytics Governance

Benefits

  • competitive benefits package
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