Analytics Engineer

We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization. We are looking for someone who can work closely with Data Scientists and Engineers across diverse areas of the organization (Consumer, Ads, and Marketing) 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.

• →Be a key contributor and collaborator to the success of data quality, performance, reliability, and automation initiatives.
• →Manage a portfolio of data products that deliver high-quality, trustworthy data
• →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.
• →Develop and implement data quality checks, conduct QA and implement monitoring routines
• →Create and manage new data integrations across internal and external systems
• →Create tools and applications for internal use that streamline data analysis and reporting. Drive widespread adoption of these tools and applications with a relentless focus on automation, consistency, and reliability.
• →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.
  
  

• Bachelor's degree in computer science or a quant educational field
• 3+ 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 analysis and dashboard design.
• Deep understanding of technical and functional designs for relational and MPP Databases.
• Proven track record of cross-functional execution and collaboration. 
• Agentic AI-assisted development experience.
• 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.
  
  

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/ 

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.