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KDnuggets Home » Jobs » Tagged: Big Data Engineer ( 14:n09 )

Tagged: Big Data Engineer

Tagged makes social discovery products that enable anyone to meet and socialize with new people. Data Engineer works very closely with Data Scientists to build high performance, high volume data engineering solutions.

Tagged Company: Tagged
Location: San Francisco and Palo Alto, CA

About Tagged
Tagged makes social discovery products that enable anyone to meet and socialize with new people. Our mission is to help everyone feel love and belonging, and we're building toward a vision where anyone can use a device to instantly connect with interesting new people anytime, anywhere.

About the Relevance Team
Social discovery is the art and science of enabling two people unbeknownst to each other to meet for the first time with an ease and elegance occasioned between friends. The Relevance Group is at the forefront of defining social discovery as a discipline, and central to its thinking is the role and purpose of content. If almost all new conversations are to occur online in the future, then real-time, broad-based context in the absence of physical presence will be based on the interpretation of social interests, mores and cues extracted from content.

About the Job
In short, the Data Engineer works very closely with Data Scientists to build high performance, high volume data engineering solutions in a highly distributed, parallel environment. The interaction between the moving parts of agile data modeling is elegantly expressed through a domain specific language that is extensible.


The Data Engineer has three main responsibilities:
  • Collection, manipulation and aggregation of data to help build features. Tagged is an event-based architecture generating gigabytes of data every few minutes. Listeners consume data for both online and offline tasks. Data for analytical purposes and model training are accessed using the Hadoop eco-system.
  • Implementation of supervised and unsupervised machine learners using Scala/Java. Many state-of-the-art machine learners do not come pre-packaged, and when they do, they are very hard to extend for our purposes.
  • High-performance execution of data models in a production environment, capable of handling thousands of requests per second.

About You
Technology is at the point where ubiquitous devices mitigate the problem of physical distance between people. In other words, the internet is part of our physical world and our physical world embraces the internet. The round-trip of reality to digital bits and back means that all life is now data - it is all about the capture, extraction, augmentation, interpretation, transformation, composition, propagation and last but not least, the volume of data. The Data Engineer will be the most important software engineering position for decades to come.

Job requirements
  • 5+ years of Java experience and some functional language programming
  • 5+ years of experience in layered architectures, components, interfaces, messaging and patterns
  • 3+ years of experience building extremely high throughput, high availability data processing systems
  • 3+ experience with relational databases
  • Good understanding of big data database architecture, indexing, and partitioning
  • Solid Hadoop stack experience (e.g. MapReduce, Pig, Hive, HBase)
  • Strong experience working with structured and unstructured data, ETL, and scripting languages
  • Interest and capability to implement state-of-the-art machine learning algorithms to production quality
  • Interest and capability to engage with data scientists in problem-solving

Education: MSc Computer Science

Reports To Data Science

  • 100% Medical For Employees
  • 75% Medical For Dependents
  • Monthly Massages
  • Catered Lunch & Dinner
  • Unlimited vacation and sick leave
  • Free Gym Membership
  • Commuter Checks
  • Volunteering opportunities
  • Employee Referral Program
  • Flexible Spending Accounts
  • 401k Plan
  • Ping Pong Tournaments
  • Field Trips
  • Fully Stocked Kitchen
  • Plus Many More...

Kendall McCann (LinkedIn), or email:

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