> Markdown version of [/jobs/ext/2720408-data-engineer-spear-ai](https://www.wearedevelopers.com/jobs/ext/2720408-data-engineer-spear-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Spear AI - **Company:** Spear AI - **Location:** Washington, DC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Cloud Computing Security, Information Engineering, Data Governance, Data Security, Decision Support Systems, Python (Programming Language), Network Security, SQL Databases, Data Processing, Data Ingestion, Apache Spark, SC Clearance, Data Management, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/mission-data-engineer-spear-ai-company-8111254 ## About the Role Active Secret clearance. 3-7 years in data engineering, preferably within secure, high-side environments. Proficiency in Python, Spark, SQL, and data orchestration tools (e.g., Airflow). Experience with classified data management, secure networking, and infrastructure optimization. Preferred Experience: Familiarity with IC standards (UDS, IC ITE) and secure cloud environments (AWS GovCloud, C2S). Strong troubleshooting and optimization skills within complex operational settings. ## Description Spear AI seeks a Data Engineer to build robust, secure data infrastructure supporting the an IC Task Force. The role involves creating resilient pipelines to power analytics and decision support systems. Primary Responsibilities: Design and manage secure data pipelines enabling ML and analytics workflows. Handle data ingestion, transformation, and validation with auditable, secure processes. Collaborate with mission engineers and data scientists to align infrastructure with operational objectives. Optimize data processing and storage for real-time and batch operations. Ensure compliance with DIA's data governance and cross-domain security standards. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)