Senior Analytics Engineer - US (Remote)

5+ years of experience as an analytics engineer, data engineer, or similar role in a SaaS environment. Deep expertise in SQL, dbt and modern data modeling best practices. Proven experience working with event-based and product usage data. Experience connecting marketing data to product analytics and building end-to-end pipelines. Comfortable with large-scale data systems (Snowflake, BigQuery, Redshift). Strong familiarity with CI/CD, Git-based workflows, and automated testing. Experience collaborating cross-functionally with engineers, analysts, and product managers. Demonstrated success using analytics to drive decisions in a technical or product-focused environment. Comfort taking ownership of ambiguous problems and designing end-to-end solutions. Proficiency in Python (Nice to Have). Experience building and maintaining Airflow DAGs (Nice to Have). Experience with Spark and PySpark (Nice to Have).

Own and evolve dbt project, ensuring models are performant, tested, and documented. Design and maintain Snowflake data warehouse and ingestion processes. Use modern data modeling best practices to create core entities and datasets. Implement testing and observability for analytics pipelines. Enforce CI/CD best practices, including automation, linting, tests, code review, and approvals. Standardize metric definitions and ensure consistent computation across tools. Act as data liaison between Engineering, GTM, and Finance. Enable stakeholder self-service access to trusted insights. Drive data literacy and evangelize best practices in querying, dashboarding, and interpreting metrics.