Sr. Analytics Engineer

• Strong expertise in SQL and BigQuery, including query optimization, partitioning, clustering, table design, and cost-performance trade-offs.
• Hands-on experience building modular, tested, and documented data models with dbt, including macros and packages.
• Proven experience working with mobile application event data and event-driven analytics ecosystems.
• Experience connecting application events with device telemetry and modeling complex event-driven data flows.
• Experience developing and maintaining semantic layers, metrics, and business dashboards using Looker and/or Power BI.
• Proficiency in Git, including version control, branching strategies, pull requests, and code review workflows.
• Experience implementing automated data quality checks using dbt tests, Great Expectations, or similar tools.
• Experience in a mobile app ecosystem involving IoT or connected devices is particularly important.

Nice to have:

• Basic scripting, API integrations, and data orchestration with Python.
• Experience with GitHub Actions or similar deployment automation tools.
• Familiarity with data pipelines that transfer events and telemetry from connected devices into BigQuery.

• Design, build, and maintain scalable data models using BigQuery and dbt.
• Transform raw mobile app events and IoT telemetry into clean, reliable, business-ready datasets.
• Develop and maintain a consistent semantic layer and business dashboards using Looker and/or Power BI.
• Optimize BigQuery queries, data structures, and processing costs.
• Implement automated data quality checks and testing frameworks to ensure data accuracy and consistency.
• Collaborate with stakeholders to translate business requirements into robust analytics solutions.
• Apply software engineering best practices, including version control, code reviews, and automated deployments.

• The role is to start as soon as possible.