In A Nutshell
Lead the development of scalable reliable data systems, including data pipelines, cloud architecture, and data storage solutions for efficient data processing, analytics, and dashboarding.
Responsibilities
- Ensure the infrastructure can support A/B testing, rapid experimentation, and model integration for AI/ML-driven features.
- Collaborate with program delivery, program design, and platforms teams, as well as other internal and external stakeholders, to gather requirements, refine application schemas, develop data models, and design analytics solutions that address specific business needs.
- Design and implement data systems that enable rapid A/B experimentation, allowing teams to quickly test new features, measure results, and iterate efficiently.
- Oversee the design and implementation of data quality assurance processes, ensuring that data is clean, accurate, and consistent across all products and regions. Implement data governance and security protocols in compliance with regional regulations to protect sensitive data and uphold privacy standards.
- Support data analysts and monitoring teams in building and maintaining dashboards to track key metrics and trends, while effectively communicating insights and challenges back to the relevant stakeholders.
- Lead, mentor, and build capacity within the data team by fostering data literacy, enhancing technical expertise, and promoting best practices.
Skillset
- 8+ years of proven experience in data engineering, analysis, data management or other equivalent fields. Experience in applying basic data science techniques (e.g. statistical modeling) to real-world product challenges, particularly in support of A/B experimentation and rapid feature testing.
- Technical expertise in data warehousing solutions, database design, advanced data modeling techniques, SQL, Python, and data manipulation languages (DML). Hands-on experience with data pipeline and ELT/ETL tools (e.g., Fivetran, Airbyte, dbt), including designing, building, and optimizing scalable data workflows. Proficiency in cloud-based data warehouse and data processing platforms (e.g., BigQuery, Snowflake, Databricks).
- Proven experience in generating actionable insights to inform strategy and product improvements.
- 2+ years in leadership roles, managing and mentoring a team of data professionals while collaborating with other leaders to achieve shared goals and drive team success.
- Strong analytical, problem-solving, and communication skills, with a keen attention to detail, self-motivation, and the ability to work effectively both independently and collaboratively within a team environment.