Analytics Engineer

• 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

Benefits

• Comprehensive health benefits
• Flexible vacation & Reddit global days off
• Family planning funds & 4+ months paid parental leave
• Personal & professional development funds
• Paid volunteer time off
• Workspace & home office benefits
• Proven track record of cross-functional execution and collaboration
• Self-starter, ability to work independently and autonomously, as well as part of a team
• Experience with data workflows (such as Airflow), data modeling, front-end or back-end engineering
• Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company, of differing levels of technical acumen
• 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
• Agentic AI-assisted development experience
• Deep understanding of technical and functional designs for relational and MPP Databases
• Bachelor’s degree in computer science or a quant educational field
• Experience with data modeling, ETL and ELT concepts, and patterns for efficient data governance. Experience with manipulating massive-scale structured and unstructured data
• Strong programming proficiency in Python, SQL, Spark, Scala, etc
• Experience in data analysis and dashboard design