Data Engineer

Company: Kinesso
Location: Walton
Posted on: February 24, 2021

Job Description:

The Kinesso Research & Development Team's mission is to produce novel and disruptive solutions in the media, advertising, and marketing technology space. We pursue this mission by identifying key industry opportunities and trends and designing new algorithmic tools using concepts from game theory, information theory, probability & statistics, reinforcement learning, nonlinear dynamics, and various other areas of mathematics, data science, and technology, to extract commercial value. At any given time, we will be developing two to four major projects with one- to two-year time horizons and a small number of faster-cycle projects with a more narrow focus. We are a small team whose existence consists mainly of pushing at high-speed down a path while simultaneously drawing the map for that path. In pursuing its mission, the Research & Development Team constantly identifies new data sources from both inside and outside the existing business and incorporates them into local platforms for use in its projects. The R&D Data Engineer will be responsible for efficiently architecting, building, and maintaining (1) the data infrastructure to enable the R&D Team's machine learning and data science specialists to build applications that use this data, and (2) the application infrastructure to optimize the R&D process and eventual handoff of R&D tools for full productization elsewhere in the company. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. They must be self-directed, comfortable working in the presence of ambiguity, and confident enough to respond to ambiguity by making a reasoned judgment, trying an optimal approach, evaluating the success or failure of that approach, and trying again if necessary.
Key Responsibilities

• Create and maintain optimal data pipeline architecture, assemble large, complex data sets that meet functional / non-functional business requirements.
• Architect application infrastructure to contain and support complex AI tools connecting reinforcement learning agents, deep neural networks, proprietary algorithms, sensitive data sources, and various external partners.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build and manage the infrastructure required for optimal automated extraction, transformation, and loading of data from a wide variety of data sources using SQL, Snowflake, and AWS 'big data' technologies, for use in speculative machine learning and AI applications.
• Collaborate with data science and machine learning specialists to produce analytics tools that utilize the data pipeline and application infrastructure to provide actionable insights into customer acquisition and implement closed-loop optimization of media buying and customer acquisition systems.
• Integrate R&D Team tools with internal and external platforms via API, FTP, and other means.
• Work with data science and machine learning/artificial intelligence experts to strive for greater functionality in our data systems. Desired Skills & Experience
  
  • Experience with cloud and container systems including AWS cloud services: EC2, EMR, RDS, S3, Redshift; Docker and Kubernetes
  • Experience with object-oriented/object function scripting languages: Python required; C++ a bonus, etc.
  • Experience designing, programming, testing, and maintaining reliable connections to RESTful APIs
  • Experience creating database stored procedures and functions
  • Experience architecting fast-cycle development for speculative applications
  • Experience with reinforcement learning environments a bonus
  • Ability to communicate, collaborate and work in ambiguous and unmapped contexts a necessity.

Keywords: Kinesso, Scranton , Data Engineer, Engineering , Walton, Pennsylvania