Defined GDPR- and PII-compliant data modeling standards and built dimensional models with SCDs to enable fast, consistent analytics. Designed and maintained 60+ batch and real-time ETL pipelines using Ruby and SQL, with custom orchestration, SLAs, monitoring, and alerting. Managed Redshift and Postgres databases, including migrations and upgrades.
Collaborated closely with software engineers on Reverse ETL, upserting aggregated data into application databases for real-time user targeting. Served as a subject matter expert on revenue-critical projects, resolving upstream data issues and delivering complex real-time logic. Owned data for application development and supported data-dependent use cases.
Developed Python automation tools that cut stakeholder manual effort by 20%. Designed and analyzed A/B tests to guide feature development and measure product impact.
Delivered executive-level reports and dashboards supporting strategic decisions, covering key metrics such as retention, conversion, LTV, CAC, ROAS, and ARPU. Provided fraud detection support for Product, Marketing, and User Acquisition teams.
Acted as a trusted data advisor and champion for data governance, fostering strong stakeholder relationships and driving data quality initiatives across teams.
Mentored team members on analytics best practices, including data modeling, schema design, and decision rationale. Led code reviews, QA’ed Tableau calculations, and helped stakeholders interpret reports and insights.
Partnered with user acquisition, product, marketing, sales, ad-ops, finance, and third-party analytics teams to clarify requirements, set data expectations, and translate business needs into technical designs. Maintained documentation and managed workflows via JIRA.
