Senior Analytics Engineer - Trust & Safety

Reddit is a community of communities. It’s built on shared interests, passion, and trust and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 101M+ daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit redditinc.com.

[Location: remote-friendly or any office location - SF, LA, CHI, NY]

We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization, focused on the Safety domain. We are looking for someone who can work closely with Data Scientists and members of Safety cross-functional teams to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s business forward and provide a data and tooling foundation that will last decades. 

Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas. 

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations, our doors are open so you can come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence

Responsibilities:

• Be the Analytics Engineering lead within the Safety organization and a key contributor to the success of Data Science data quality, performance, and automation initiatives. 
• Be the data steward for Safety: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for business tracking, ML model development, and other data-driven capabilities.
• 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.

Required Qualifications:

• Experience working in a Trust and Safety domain
• Undergraduate degree in a quantitative discipline: engineering, statistics, operations research, computer science, informatics, applied mathematics, economics, etc. 
• 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, 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, of differing levels of technical acumen
• Experience in mentoring junior data scientists and analytics engineers
• Self-starter, ability to work independently and autonomously, as well as part of a team

Nice to have:

• M.S. or Ph.D. in a quantitative discipline 
• Past experience collaborating closely with data scientists, machine learning engineers, and product managers 

Benefits: