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“The front page of the internet," Reddit brings over 430 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities.
Who We Are
Advertising is Reddit’s primary business model and we have an ambitious goal to turn it into a massive business to fund Reddit’s mission to bring community and belonging to everyone in the world. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities that drive action. This large number of self-governed communities have highly-engaged users who are in an unduplicated mindset of consuming relevant information. This has created the opportunity for Reddit to build a massive and highly differentiated ads business.
Reddit is continuing to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.
As the Engineering Manager of the Ads Marketplace Quality team. You will work closely with Product owners and Data Scientists from our Ads team to 1) set up the vision and product strategy of ads quality and relevance, 2) optimize ads delivery and auction systems through utility function design, 3) measure various marketplace tradeoffs. This person is an industry leader in the online ads marketplace optimization domain with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills.
What You’ll Do
Ads Marketplace Quality Technical Vision
Your primary mission will be to build the auction/ranking platform for Ads Marketplace Quality that can scale with our ads business over the next several years. There is plenty of room for guiding and setting technical vision that will have a huge impact on our business.
You will own the execution of your team’s roadmap and be accountable for consistent, predictable delivery. You will ruthlessly prioritize both planned projects and emergent asks. You will coach Tech Leads on project management and empower your team to execute autonomously. You will identify risks and proactively communicate them both internally and externally.
Ads Marketplace Quality will grow quickly during your tenure at Reddit, and our engineering managers are directly responsible for scaling up their teams. You will identify your team’s needs, write job descriptions, source, interview, and help close candidates. You will have the support of our incredible recruiting team to bring diverse and talented engineers into Reddit.
You will help your engineers identify career goals and create development plans to achieve them. You will constantly seek opportunities to push your engineers outside their comfort zone and turn followers into leaders.
You will work with your team to develop processes and tooling that constantly improve the quality of our products and systems, ensuring that they meet product requirements, customer needs, and SLAs.
You will serve as a thought partner to product and upper management to ensure your team’s plans align with company goals. You will become an expert in the digital ads business and our customer needs. You will participate in and challenge prioritization decisions. You will communicate your team’s work and set expectations with external stakeholders.
- 2+ year of supporting and growing engineering teams - ideally hiring and scaling a team over 100% growth
- Experience managing a team including hiring, onboarding, and professional development
- You're technical, enough to solve almost any problem your team has yourself, but you prefer to guide your team into solving them
- Excellent written and verbal communication skills. You must be able to collaborate effectively with teams in a fully-remote environment and discuss complex topics with technical and non-technical audiences
- Experience with data driven/informed decision making
- Familiarity with the team’s tech stack, or a proven history on quickly reaching proficiency in unfamiliar tools/languages
- Languages: Golang, Scala
- Frameworks: Thrift, Baseplate, Kafka
- Datastores: Postgres, Druid, Redis, BigQuery
- Tools: Kubernetes, Airflow, Docker
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