Position Overview

Buzzer is seeking an experienced Data Engineer with backend engineering experience to join Buzzer in support of the productization of our proprietary algorithms that power the Buzzer application. This is a critical role on our engineering team to build a scalable and accurate solution to serve customers personalized notifications regarding upcoming, interesting live sports streams. This role will be essential to building out our backend systems as we partner with various sports leagues and data providers, each with their own sets of specs and requirements.

This role is focused on developing, supporting, and enhancing the data pipelines for our ‘Buzzer Moment’ algorithm (which varies by league) leveraging cloud services on AWS. This role sits within an engineering organization of data scientists, mobile, platform, and quality engineers, and will help enhance the transformation of raw data into mature models for deployment and the input for additional downstream infrastructure. As Buzzer continues to scale, the scope of this role will include the efficient implementation of data models in the cloud as well as performance optimization of existing data pipelines. 

In addition to cloud services and data engineering experience, this individual should be highly self-motivated, able to effectively manage one’s own time, extremely collaborative, and highly communicative especially given our distributed team.

Buzzer is presently a fully distributed company (though subject to change). The Data Engineer reports directly to the Engineering Manager (Data), sits on the Data team, and works directly with the Engineering and Product teams composed of our Product Managers, UX Designers, and engineers, and collaborates with the broader Operations and Partnerships teams.

In this role, you will:

• Data Pipeline Cloud Implementation: Partner with Lead Engineers on the identification and implementation of effective cloud solutions supporting the data extraction, transformation, and loading of our models for detecting ‘Buzzer Moments’ (e.g., moments that trigger notifications based on performance criteria). Drive the creation and management of our data pipeline, lifecycle, and processes.

• Cloud Architecture: Support Data Scientists in migrating local data models to a distributed cloud environment to allow Buzzer to scale at a production level and reuse infrastructure across leagues through modular design.

Required Qualifications

• 2+ years of work experience developing and managing scalable ETL data pipelines in the cloud (ideally within AWS)
• 2+ years of work experience as a Data Engineer with proven expertise in at least one database and warehousing technology, such as Snowflake, Hadoop, EMR, Redshift, Spark, or Scala and one ML model implementation
• 2+ years of work experience with backend engineering development
• Experience preparing and transforming (un)structured datasets for use in ML models and algorithms
• Experience in building highly available distributed systems of data extraction, ingestion and processing of large data sets
• Experience building data flow in machine learning pipelines, particularly for recommendation engines and real-time estimation/prediction algorithms, and natural language processing
• Strong experience with Python, SQL, NoSQL, REST APIs, containerization, parsing of various data formats
• Strong analytic skills related to working with unstructured datasets and determining root-cause
• Experience in stakeholder management and proven communication skills with both business and technical teams
• Fluency in English

Preferred Qualifications

• Experience working with AWS, with a strong understanding of DynamoDB, S3, Redshift, ECS, Step Functions etc.
• Experience working with both supervised and unsupervised machine learning models
• Experience working with ML libraries/frameworks such as AWS Sagemaker, Tensorflow, Keras, etc
• Experience in operating multi-level abstraction when training and deploying machine learning models
• Experience working with container workflows/execution, and serverless cloud compute, (ECS, Docker & Lambda)
• Experience working in an agile environment with 2-week sprints
• Experience with sports media applications and or design