• MS or PhD in a quantitative discipline: engineering, statistics, operations research, computer science, informatics, applied mathematics, economics, etc
• 7+ years of experience working with large-scale ETL systems (implementation, strategy, and maintenance), building clean, maintainable, object-oriented code (Python preferred) in a production environment
• Strong programming proficiency in Python, SQL, Spark, Scala, etc
• Experience with data modeling, ETL (Extraction, Transformation & Load) 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, including tools such as Looker, Tableau, R visualization packages, streamlit, D3, and other libraries, etc
• 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
• Experience in mentoring junior data scientists and analytics engineers
• Self starter, ability to work independently and autonomously, as well as part of a team

Desirable

• Act as the analytics engineering lead within Ads DS team and a key contributor to the success of data science data quality and automation initiatives
• You will have a keen interest in the collection and quality of underlying data (experiment design and analysis, data deep dive) and in working on ETLs, reporting dashboards, and data aggregations needed for business tracking and/or ML model development
• 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. Driver widespread adoption of these tools and applications
• 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 analysts
• 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