Field Engineer, Data Engine

You will:

Be open to >50% onsite work in a secured space.
Collaborate with cross-functional teams to define and execute the vision for data pipelines and agents.
Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
Deploy and maintain Scale software at customer sites.
Develop customer requested features and work closely with them to ensure that they win customer love.
Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
This role will require at minimum an active Secret clearance and willingness to obtain a TS/SCI security clearance.

Ideally you have:

Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
Prior experience developing with Python
Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
Linux experience: Understanding of shell scripting, operating systems, etc
Networking experience: Understanding of networking technologies, configuration (ports, protocols, etc) is a plus.
Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles