Data & Analytics Engineer

Builds and maintains the data pipelines and reporting layer that make Redis's marketing data trustworthy enough to make decisions on: moving, transforming, and building trust in data from the moment it's captured through every transformation to the point someone (or some agent) relies on it.

What you'll do

• Run data movement and transformation into the warehouse so downstream reporting reflects reality without manual patching or "fix it in the spreadsheet" workarounds.
• Build and maintain attribution and measurement models, reconciling online and offline conversion events across systems.
• Build and maintain the dashboards and reporting used across the team, and proactively flag data-quality issues before they surface in a leadership review.
• Partner directly with Josh (AI Engineer, Ops Support) on the shared context engine that other agents across the team read from.
• Document data definitions and lineage clearly enough that someone outside this role can trust and use the numbers without re-asking where they came from.

About you

• Analytics-engineering background: comfortable with data transformation (dbt-style modeling) and warehouse concepts, not just SQL for one-off pulls.
• Comfortable owning data quality end to end rather than just querying whatever's already in a table.
• Experience reconciling attribution across online and offline conversion sources.

Nice to have: experience building data infrastructure that feeds both BI dashboards and AI/agent systems; familiarity with reverse-ETL or activation tooling.