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About
Location:
Onsite | Boston, MA or New York, NY Clearance:
Must be a U.S. Person; ability to obtain a Secret or Top Secret/SCI security clearance preferred Employment Type:
Full-time, salaried, with full benefits
The company & Mission:
Our client is a fast-growing, venture-backed startup building the AI operating system for federal procurement and capture.
Founded in 2022 and backed by Andreessen Horowitz (a16z) along with other leading venture investors, the company is connecting missions, markets, and people to power the future of national security. They unify fragmented workflows, siloed data, and dispersed human networks into a single, actionable platform used across the U.S. national security ecosystem.
Built by alumni of leading Silicon Valley technology companies and major defense organizations, the team operates with urgency, high ownership, and a deep sense of mission - bringing modern AI, data, and software workflows into one of the most complex and consequential markets in the world.
What This Role is All About:
We're hiring a hands-on Data Engineer to design and scale the data backbone of the platform.
This is a foundational role. You will own production-grade data pipelines and warehouse architecture, ensure data reliability and correctness, and power the intelligence layer that drives AI workflows, CRM systems, and budget intelligence capabilities.
You'll work directly with product, engineering, and federal domain experts to ingest, model, and serve complex public and proprietary datasets - enabling customers to discover opportunities, understand funding flows, and act with precision.
This role is ideal for a mid-to-senior engineer who thrives on ownership, cares deeply about data quality, and wants to build durable systems in a high-velocity startup environment.
What You'll Be Doing:
Design, build, and maintain scalable ETL/ELT pipelines across structured and unstructured data sources Architect and manage data warehouse and storage systems (e.g., S3, Postgres, Snowflake, BigQuery, etc.) Own orchestration frameworks (Airflow, Prefect, Dagster, Temporal, etc.) and ensure production reliability Develop ingestion systems for APIs, web data, real-time feeds, and customer integrations Implement robust data modeling to power analytics, search, AI discovery, and CRM workflows Improve observability, testing, and monitoring for data correctness and uptime Partner closely with product and AI teams to enable advanced analytics and LLM-driven workflows Contribute to backend systems and infrastructure as needed Participate in on-call rotation for data infrastructure
What You Bring:
Based in Boston (preferred) or NYC, or willing to relocate 4-7+ years of professional data engineering or backend engineering experience Demonstrated ownership of production-grade data systems and pipelines Strong Python and SQL skills for data processing and modeling Experience building ETL/ELT pipelines and working with large-scale datasets Experience with orchestration tools (Airflow, Prefect, Dagster, etc.) Experience with cloud infrastructure (AWS, GCP, or Azure) Comfort working in a fast-paced, ambiguous startup environment Strong ownership mentality - able to independently design and ship systems
Bonus Points:
Experience with Spark, distributed systems, or streaming systems (Kafka, RabbitMQ, etc.) Experience building AI/LLM data workflows Experience building internal data platforms from scratch at a startup Previous startup or early-stage engineering experience Interest in defense, national security, or dual-use technology Demonstrated builder energy (side projects, open-source contributions, or founding experience)
Benefits:
Competitive salary & meaningful equity Health, dental, and vision coverage PTO + holidays Work at the intersection of AI, software, and national security Join a small, high-ownership engineering team
Languages
- English
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