Location: US Remote friendly
Reddit has a flexible first workforce
Reddit is poised to rapidly innovate and grow like no other time in its history, and user safety is a critical accelerant of that growth. As an analytics engineering lead on the Safety data science team, you will achieve Reddit-wide impact through leading a team of full-stack data scientists and performing hands-on execution. You will create a first-class Safety data warehouse and data tools, to provide customized solutions and meet a wide range of evolving needs, including scalable and high-quality metric reporting, regulatory compliance, product insights, and enforcement insights. You will play a critical role in showcasing the impact of Safety, and unlocking innovation in protecting good users from bad experiences. If you are passionate about building high-quality data products, leading strategy to build an agile but reliable foundation to accelerate Safety at Reddit, and working with a scrappy and supportive team, then Reddit will be the perfect home for you.
We are hiring a Senior Analytics Engineer who can translate diverse data needs into data models and tooling design, drive org-wide data foundation strategy, and make ambitious technical visions come true. You will be exposed to the full lifecycle of data at Reddit, and you will leverage one of the largest and richest datasets in the world.
Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to 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 from anywhere in the United States.
Responsibilities:
- Understand data user needs to design data pipelines and tooling, with stakeholders including: Safety data scientists who partner with Enforcement, Product and Engineering teams, Trust & Safety Policy, and Legal
- Own and improve metric reporting, metric validation and new metric development for Reddit’s transparency reporting and regulatory reporting
- Audit and revamp existing data warehouse with a focus on improving data quality, data trustworthiness and pipeline observability
- Increase the Safety data science team’s efficiency through automation, ETL frameworks and scalable processes
- Collaborate with company-wide data science teams in building shared data frameworks and tooling
Required Qualifications:
- Python proficiency and strong SQL proficiency.
- 4+ years experience working with large scale ETL systems (implementation, strategy, and maintenance).
- 4+ years of non-internship professional experience building clean, maintainable, object-oriented code (Python preferred) in a production environment.
- Experience as database administrator or architect with large-scale data warehouse systems like Google BigQuery.
- Excellent communication skills to collaborate with cross-functional stakeholders at all levels of the company.
- Preferred: Proficiency with Airflow or similar data/ETL tools in a production environment.
- Preferred: Experience with public / regulatory metric reporting
Benefits:
- Comprehensive Healthcare Benefits
- 401k Matching
- Workspace benefits for your home office
- Personal & Professional development funds
- Family Planning Support
- Flexible Vacation (please use them!) & Reddit Global Wellness Days
- 4+ months paid Parental Leave
- Paid Volunteer time off
Pay Transparency:
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 pay 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.
