Title: Analytics Engineer Location: Toronto, Canada Job Description: 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 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com. Analytics Engineer - Consumer Data Science Check out our r/RedditEng post to learn more about the team, and what we do: https://www.reddit.com/r/RedditEng/comments/1mnmf71/analytics_engineering_reddit/ On Reddit, people can dive into anything through experiences built around their interests, hobbies, and passions. Our mission is to empower communities and make their knowledge accessible to everyone. With over 100,000 active communities and over 120 million daily active users, it is home to the most open and authentic conversations on the internet. Reddit’s unique and differentiated product is extremely attractive to advertisers, who can reach out to and connect to our users authentically. 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 Consumer domain. We are looking for someone who can work closely with Data Scientists and members of Consumer cross-functional teams (Product, Engineering, and Design) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base. 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 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. Benefits: - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Comprehensive Medical Benefits & Health Care Spending Account - Registered Retirement Savings Plan with matching contributions - Income Replacement Programs - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave #LI-REMOTE In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors. Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

• Design, build, and evolve high-scale dbt models that transform raw upstream inputs into clean, well-documented, analytics-ready data products with clear contracts and ownership. • Implement critical guardrails, clear grain definitions, meaningful metadata descriptions, and approved access paths so AI tools and agents can query data accurately without bypassing governance. • Shape how metrics are defined and exposed so that analysts, dashboards, and AI tools all return the same answer to the same question, turning the semantic layer into production-grade infrastructure for AI-powered BI. • Translate recurring analyst pain points—such as ambiguous metrics, broken joins, or undocumented fields—into durable, reusable models, patterns, and shared interfaces. • Set and hold the bar for what "done" means for a data product, embedding robust testing, freshness expectations, data catalogs, and metadata ownership into the development lifecycle. • Coordinate across data platforms and product teams to map use cases, eliminate duplicate work, surface technical tradeoffs early, and drastically reduce cycle times from business question to trusted answer. • Collaborate with data and analytics engineering peers to establish and maintain global patterns, package management, and repository best practices. • Raise the collective engineering bar across the organization by running technical reviews, hosting office hours, and leading pair-programming sessions with domain analysts and engineers.

• Seeking to hire a Senior Analytical Engineer - Contractor based out of Mexico or Argentina for Newsela's Internal Data Team. • We are looking for a Senior Analytics Engineer to join our data team. • Reporting to the Hiring Manager, you will be responsible for applying data engineering best practices to analytics code to transform, test, and document data. • You will provide clean and organized data sets to end users. • You will be provide expert code reviews and mentorship to other engineers in the data space. • You will be responsible for building and maintaining composable data models, as well as optimizing SQL query performance for the models you build. • You will transform raw data into business insights, working closely with stakeholders and developing analyses to answer critical business questions. • You will create data visualizations and help stakeholders explore and understand the data visualization tools available to them.

• Be the Analytics Engineering lead within the Sales and Marketing organization and a key contributor to the success of Data Science data quality, performance, and automation initiatives. • Be the data steward for Sales and Marketing: architect and improve the collection of underlying data while also creating ETLs, reporting dashboards, data aggregations and other deliverables needed for business tracking, advertiser outreach and acquisition, marketing campaigns, and 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.