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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Product Analytics Engineer - **Company:** Altium Limited - **Location:** San Diego, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Business Analytics Applications, Data Analysis, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Distributed Systems, Raw Data, Software Engineering, Web Applications, Usage Analysis, Sql Optimization, Backend, Data Lakes, Data Analytics, Data Management, Data Pipelines - **Published:** September 3, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3375520155&tx=KJ6969FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 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. ## Description 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. Key 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 Expected Outcomes The successful candidate will establish a clear and reliable analytics platform where * Product teams have a standardized way to instrument new functionality. * Analytics events are consistently defined and documented. * Data reliably reaches the analytics platform from production systems. * Raw data remains available for investigation and reprocessing. * Transformations and aggregations are automated and maintainable. * Important metrics have clear and consistent definitions. * Data quality issues are detected proactively rather than discovered through incorrect dashboards. * Business and product teams can confidently use analytics tools for decision-making. * Every important metric can be traced back to its underlying product events and data sources. * The analytics platform has clear technical ownership. ## Related Videos - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Analyst Salary Germany](https://www.wearedevelopers.com/magazine/277-data-analyst-salary-germany) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market)