About the Role
This role involves building and optimizing analytics infrastructure to uncover patterns in member activity, supporting business units with reliable, actionable insights derived from complex data ecosystems.
Responsibilities
- Develop and manage scalable data pipelines for member behavior analytics
- Design data models that support long-term insight generation
- Collaborate with product and engineering teams to define key metrics
- Ensure data accuracy and consistency across reporting systems
- Optimize ETL workflows for performance and reliability
- Identify opportunities to improve data quality and coverage
- Support the creation of dashboards and self-service analytics tools
- Work with large-scale datasets in distributed environments
- Implement data validation frameworks to maintain integrity
- Translate business questions into analytical solutions
- Maintain documentation for data assets and processes
- Drive automation of recurring analytical tasks
- Partner with stakeholders to understand insight requirements
- Evaluate new data sources for integration potential
- Monitor pipeline health and troubleshoot issues
- Contribute to data governance and access policies
- Use SQL and programming languages for data transformation
- Support A/B testing frameworks with robust data setups
- Ensure compliance with data privacy standards
- Mentor junior engineers on best practices in analytics engineering
Nice to Have
- Experience in member or user behavior analytics
- Familiarity with real-time data processing systems
- Knowledge of machine learning pipelines
- Experience with data lineage tools
- Background in subscription-based or digital services
Compensation
Competitive salary based on experience and location
Work Arrangement
Hybrid work model with flexible scheduling
Team
Part of a high-impact engineering team focused on data and insights
Why This Role Matters
Your work will directly influence how the organization understands member engagement and retention. By building robust analytics systems, you enable faster, better decisions across product and business functions.
Technology Stack
We use modern cloud data platforms, automated pipeline orchestration, version-controlled data modeling, and scalable query engines to power insights at volume.
