Analytics Engineer

Responsibilities

• Be an Analytics Engineering leader within the Consumer organization and a key contributor and collaborator to the success of Data Science data quality, performance, reliability, and automation initiatives.
• Be the data steward for Consumer products: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for product feature tracking, user retention analysis, A/B testing, and a large number of other data-driven activities.
• Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines.
• Create user-friendly tools and applications for internal use across Data Science and cross-functional teams, streamlining data analysis and reporting processes. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.
• Lead transformational efforts to build a data-driven culture at Reddit by enabling data self-service.
• Provide technical guidance, mentorship, coaching and/or training to data scientists and other technical partners.
• Serve as a thought partner for data scientists, engineering managers, and leadership on data foundations, communicating and shaping the data foundations roadmap and strategy for Reddit.

Qualifications

• Degree in a quantitative discipline such as statistics, operations research, computer science, applied mathematics, economics, or physics
• 4+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable code and systems (Python preferred) in a production environment.
• Strong programming proficiency in Python, SQL, Spark, Scala, etc.
• Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data.
• Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering.
• Experience in data visualization and dashboard design.
• Deep understanding of technical and functional designs for relational and MPP Databases.
• Proven track record of cross-functional execution and collaboration. Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen.
• Self-starter, ability to work independently and autonomously, as well as part of a team.
• Consumer product domain experience is a big plus.
• Agentic AI-assisted development experience.