Staff Analytics Engineer, Ads

Reddit is poised to rapidly innovate and grow like no other time in its history and the Ads team fuels that growth. As an Analytics Engineering lead on the Ads Data Science team, you will achieve a Reddit-wide impact by leading a team of full-stack data scientists and performing hands-on execution. You will create a first-class Ads data warehouse and data tools to provide scalable solutions that meet a wide range of evolving needs - including high-quality metric reporting, product insights, and data engineering for ML models. You will play a critical role in making ads data more accessible across reddit - unlocking innovation through the self-service of our data from Engineering to Sales teams.

Responsibilities: • 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. • Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. • Create user-friendly tools and applications for internal use across Data Science and cross-functional teams. • 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.

Required Qualifications: • MS or PhD in a quantitative discipline • 7+ years of experience working with large-scale ETL systems • Strong programming proficiency in Python, SQL, Spark, Scala, etc. • Experience with data modeling, ETL concepts, and patterns for efficient data governance • Experience with data workflows, 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 • Experience in mentoring junior data scientists and analytics engineers

Nice to have: • Ads domain experience • Past experience collaborating closely with data scientists, machine learning engineers, and product managers