Senior Analytics Engineer - US (Remote)

Must Have:

• 5+ years of experience as an analytics engineer, data engineer, or a 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 (e.g., Posthog, Mixpanel).
• Experience connecting marketing data (paid ads, campaigns, attribution) to product analytics–ideally having built end-to-end pipelines from ad platforms through to conversion and retention metrics.
• 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.

Nice to Have:

• Proficiency in Python for deeper analysis and automation.
• Experience building and maintaining Airflow DAGs.
• Experience with Spark and PySpark.

What Success Looks Like

• Establish a trusted, well-modeled analytics layer that product managers, marketers, and leaders rely on daily.
• Improve data quality and reliability, with clear SLAs and observability around our most critical models.
• Drive down time-to-insight by enabling self-serve access to high-quality datasets and metrics.
• Extreme ownership over critical infrastructure and data models that directly impact product decisions and business growth.
• Partner with data engineers and analysts to build a semantic layer that AI can use to answer stakeholder questions.