Role Description & Responsibilities
Data Engineering
About Scale AI
Scale AI is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Data Engineering role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
Scale AI is seeking a highly skilled and motivated AI Data Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.
Key Responsibilities & Day-to-Day Scope
- ✓ 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.
Official Qualifications & Technical Requirements
- • 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
Preferred Skills & Technology Stack
- + Experience with big data tools (Apache Spark, Kafka, Flink) and cloud platforms (AWS, Azure, GCP).
- + Familiarity with dbt (data build tool) for SQL transformations.
- + Hands-on experience with Docker and Linux system administration.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Scale AI
Verified EmployerScale AI champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.