Software Engineer - Ads Data Infrastructure
Note: This is not an entry-level position. Applicants with experience beyond these qualifications may be considered for this role at a more senior level.
Who We Are:
Our engineering teams are responsible for monetizing the services and infrastructure that connect hundreds of millions of active Twitter users to real-time information about what’s relevant in their lives and the world we live in. We work on some of the world’s largest distributed systems -- our core infrastructure receives hundreds of millions of tweets per day and serves tens of billions of API requests, all with an uptime in excess of 99.9%. Our other systems operate at a similarly staggering scale: we serve over 2+ billion search queries per day, render hundreds of millions of ad impressions, process hundreds of terabytes of log and interaction data daily to drive billions in bottom-line revenue.
The Ads Data Infrastructure team builds the highest performance, scalable and reliable data infrastructure in the world to process the billions of events and petabytes of data generated to provide real-time insights into our advertising products.
First, build extremely scalable data pipelines and apply them to aggregate the company’s most critical real-time data that advertisers rely on. No room for discrepancies: companies make multi-million dollar decisions every day based on the results that we show them.
Second, campaign forecasting infrastructure: predict outcomes and reach even before a campaign begins. Scalable and accurate forecasting is a huge challenge to perform accurately and efficiently, and is essential to enable advertisers to confidently spend money on Twitter.
Finally, core reusable data service infrastructure which wraps any relational database in a Thrift service layer, making it possible for a diverse set of cross-datacenter readers and writers to work concurrently on core ads campaign data, the most critical and important data in our system.
If you are interested in working with the most cutting-edge and contributing to the most interesting open-source and internal technologies (Hadoop, Summingbird, Heron, Kafka, MySQL, Aurora, and others) to solve a wide range of hard problems ranging from big data and systems to prediction, this is the team for you
What You'll Do:
Analytics Infrastructure -- Build data infrastructure to make it extremely simple to obtain insights from the wealth of data that Twitter stores in its global datacenters. Apply your expertise in distributed databases and large scale systems to simplify the immense complexity of wrangling with humongous amounts of underlying data, enabling Twitter to be more agile. Dramatically improve the reliability and scalability of Analytics systems to enable Twitter to deliver solutions to the vibrant ecosystem of advertisers around the world
Forecasting infrastructure -- Revamp Twitter’s core campaign-forecasting infrastructure to predicts outcomes and reach even before an advertiser starts a campaign on Twitter. Work with large-scale systems, Hadoop and Lucene to build highly scalable indexes to forecast potential reach. Use your expertise with Big Data to improve advertiser satisfaction by providing them accurate estimates for their campaigns during campaign creation, and also help Twitter by reducing the number of under-delivering campaigns due to a mismatch b/w targeted audience and budget.
Dataservice Infrastructure -- Build core reusable infrastructure that provides a unified access layer for storing and retrieving core Ads campaign data - the most critical data in Twitter’s systems. The Dataservice is a shared multi-tenant service that forms the backbone of several of Twitter’s key advertising products
You're someone with a lot of potential who is constantly looking for real engineering challenges to tackle and hard problems to solve. You want to own significant projects while working in small teams of highly-talented, passionate engineers. The prospect of getting to work with an open-source tech stack that powers a solution people around the world love to use, and where massive volumes of data are extracted in real time excites you. You want to be mentored by amazing engineers; you want to see continued investment in you by the business; and you expect excellence in everything. You see your future self as a force multiplier (and not just a great technical resource for an employer). You see challenge as opportunity and you're looking to jump ahead of the pack in your career. You're applying to this role because you're hoping for a chance to jump in and see what you can do to make a difference in an iconic software company.
Backend development experience with a strong interest in work involving data pipelines, distributed systems, performance analysis, and/or large-scale data processing
Experience with software engineering practices (e.g. unit testing, code reviews, design documentation)
Strong algorithms and data structures background
BS, MS, or PhD in Computer Science or equivalent work experience
Experience designing fault-tolerant distributed systems
Experience with data pipelines
Experience with Hadoop or other MapReduce-based architectures
Experience with Storm or other Streaming Compute based technologies
Experience with Cassandra, Redis, Memcached or MySQL
Contributions to the open-source community
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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