Data Team Mission

Our mission on the Data Team is to bring value through data. We handle everything from schema design and streaming architecture to writing data management applications that enable world-class operations and monitoring of our robotic systems. We collaborate with teams across the organization, from internal machine learning groups to customer-facing teams, leveraging our expertise to help them achieve their goals.

Role Description

As a Data Infrastructure Software Engineer on Berkshire Grey’s Data Team, you will improve, manage, and own data systems used across the company. You will collaborate with various internal customer teams, ensuring a high level of service for both our internal and external customers.

Responsibilities

• Develop software for data backup and management for on-premise robotic systems.
• Design and build data pipelines to transform and transfer data to our data warehouse.
• Advise internal customers and product teams on schema design, data APIs, and query/analysis needs.
• Collaborate with our DevOps team to design and manage MongoDB, Kafka, and other components in Kubernetes, both in the cloud and at the edge.
• Work with our Machine Learning team to automate and manage Machine Learning operations, enabling a high-throughput Machine Learning training and evaluation pipeline.

Background and Experience

Required

• 3+ years of experience working with databases and/or data streaming platforms.
• 3+ years of experience with an object-oriented programming language, preferably Python.
• Experience developing in a Linux environment, using Git and GitHub, and utilizing a work tracking system such as Jira.
• Demonstrated understanding of data schemas and basic schema design.
• Proficiency and in-depth understanding of one or more databases, including MongoDB, Elasticsearch, and SQL databases.
• Understanding of the differences and trade-offs between SQL and NoSQL databases.

Preferred

• Experience using Snowflake as a data warehouse.
• Familiarity with Apache Kafka.
• 3+ years of experience with Python.
• Familiarity with Docker and building Docker images.
• Understanding of Kubernetes concepts, with experience deploying applications to Kubernetes.
• Experience building systems with AWS and/or GCP.

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