Responsibilities
- Serve as a senior BI partner for the Product team, owning data architecture, guiding data strategy, pipeline reliability, and the analytics engineering roadmap in support of business unit goals.
- Collaborate and consult directly with business teams to understand their strategy, economics, and goals, translating business questions into analytical frameworks.
- Design, build, and maintain scalable data pipelines and transformation layers (such as dbt models and ELT workflows) that power dashboards, reports, and ML features.
- Develop and maintain data marts, semantic layers, and self-serve tooling that empowers internal stakeholders to make smarter, faster decisions.
- Partner with analysts and product managers to instrument, design, and support A/B testing frameworks and experimentation infrastructure.
- Monitor data pipeline health by proactively identifying data quality issues and implementing robust observability and alerting frameworks.
- Work closely with data governance and data engineering to ensure data quality, lineage, and strict compliance with organizational standards.
- Apply ML engineering practices to productionize predictive models, support feature engineering pipelines, and facilitate audience segmentation and targeting workflows.
- Champion engineering best practices including peer code reviews, CI/CD for data pipelines, version control, and documentation standards.
- Stay informed about emerging trends in data science, analytics engineering, and the modern data stack.
