Staff Software Engineer

TVision is building the next generation of TV and video audience measurement, utilizing advanced data collection tools to provide insights into viewer engagement. They are seeking a Staff Software Engineer to develop and maintain backend services and data pipelines that support their measurement devices and data analysis tools.

Responsibilities:

• Build and maintain web services that support configuration, monitoring, and data ingestion for TVision's in-home measurement devices
• Build and maintain data pipelines to support the recognition and analysis of content captured by our devices
• Work with data science and analytics staff to build clean, well-designed tools and libraries for our back end data processes, making best practices in software engineering and database performance accessible to the entire team
• Ensure the quality, security, and timeliness of our data deliveries by thorough testing, careful code review, and robust operational monitoring

Requirements:

• Bachelor's degree in computer science or an allied quantitative field
• 8+ years experience in back end services development
• You should be familiar with architecture and deployment patterns for container-based, cloud provider-hosted web services, and also for batch and streaming data processing pipelines
• Experience with relational databases and data lake technologies, including reliability and performance management
• Experience with at least one modern big data processing framework, and familiarity with the landscape of technology choices. We use Spark and are migrating to Databricks. Your experience doesn't have to be that, but you should be able to compare the consequences of different framework and design choices
• Modern Python best practices. We write our code in Python because that's where the data analysis world is, but given that, we want that code to be as clear and reliable as we can manage
• Devops tools and practices, particularly on AWS. We expect all of our back end developers to understand and participate in the deployment life cycle for their work
• Comfort with quantitative data analysis methods. This isn't a data scientist position, but you will find yourself collaborating with our data science team to find the best way to carry out a computation efficiently