Data Engineer - Applied AI Engineering Group

At Dream, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; it’s a Dream job. Dream is where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Let’s build something extraordinary together. 

Dream's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our Dream's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.  

At Dream, our talented team, driven by passion, expertise, and innovative minds, inspires us daily.  We are not just dreamers, we are dream-makers. 

The Dream Job

It starts with you - an engineer who cares about building data pipelines and models that deliver reliable, trusted data. You value data quality, clean transformations, and making data accessible to those who need it. You’ll work alongside experienced engineers to build ETL/ELT pipelines, maintain dimensional models, and implement quality checks that turn raw data into actionable intelligence. 

If you want to grow your skills building data products for mission-critical AI, join Dream’s mission - this role is for you. 

The Dream-Maker Responsibilities

• Build and maintain ETL/ELT pipelines using platform tooling - workflows that extract from sources, apply transformations, and load into analytical stores. 
• Develop and maintain data models - fact/dimension tables, aggregations, and views that serve analytics and ML use cases. 
• Implement data quality checks - validation rules, tests, and monitoring for data freshness and accuracy. 
• Maintain documentation and lineage - keeping data catalogs current and helping consumers understand data sources and transformations. 
• Work with stakeholders to understand data requirements and implement requested data products. 
• Troubleshoot pipeline failures - investigating issues, fixing bugs, and improving reliability. 
• Write clean, tested, well-documented SQL and Python code. 
• Collaborate with Data Platform on tooling needs; work with Datastores on database requirements; partner with ML, Data Science, Analytics, Engineering, and Product teams on data needs. 
• Design retrieval-friendly data artifacts - RAG-supporting views, feature tables, and embedding pipelines - with attention to freshness and governance expectations. 

The Dream Skill Set

• 3+ years in data engineering, analytics engineering, BI development, or software engineering with strong SQL focus. 
• Strong SQL skills; complex queries, window functions, CTEs, query optimization basics 
• Data modeling - Understanding of dimensional modeling concepts; fact/dimension tables, star schemas 
• Transformation frameworks - Exposure to dbt, Spark SQL, or similar; understanding of modular, testable transformations 
• Orchestration - Familiarity with Airflow, Dagster, or similar; understanding of DAGs, scheduling, dependencies 
• Data quality - Awareness of data validation approaches, testing strategies, and quality monitoring 
• Python - Proficiency in Python for data manipulation and scripting; pandas, basic testing 
• Version control - Git workflows, code review practices, documentation 

Never Stop Dreaming...

If you think this role doesn't fully match your skills but are eager to grow and break glass ceilings, we’d love to hear from you! 

Requirements