Data Architect

Role overview A Data Architect role shaping large-scale, cloud-native data and AI solutions for federal clients, turning complex datasets into accessible, analytics-ready formats. The position blends architecture strategy with hands-on platform work, helping clients build flexible, resilient, and cost-effective data products tied to measurable mission value. It involves partnering across technical and non-technical audiences to translate business needs into scalable data architectures.

Responsibilities - Drive data and AI architecture and technology decisions for scalable solutions or products. - Provide insights that shape the overall strategy and roadmap for cloud-hosted data platforms. - Educate clients on crafting highly scalable, flexible, resilient, secure, and cost-effective architectures. - Connect data and AI technology choices to measurable business value and outcomes. - Identify and investigate emerging data, AI, and open-source tools and technologies. - Translate client needs into digestible technical and data requirements.

Requirements - Experience communicating with both technical and non-technical audiences. - Experience designing cloud-hosted data services on platforms such as AWS, Azure, or GCP. - Hands-on experience with ETL processes, data warehousing, and big data technologies. - Proficiency in data modeling, database design, and data governance practices. - Experience with data integration, data quality, and data security best practices. - Experience with modern data platforms such as Databricks, Snowflake, or Palantir. - U.S. citizenship required; dual citizenship not permitted.

Nice to have - Cloud-first solution delivery experience and building platforms by writing scripts or software. - Background in software development, systems engineering, infrastructure, security, or networking. - Proficiency in programming languages such as Python, Java, or Scala, plus strong SQL skills. - Experience creating data platforms and automating data processes through scripting or software development. - Familiarity with machine learning frameworks and tools such as TensorFlow, PyTorch, or Scikit-Learn.

Benefits and work setup - Listed base compensation range of approximately $126,300–$243,100 USD for specified U.S. locations, varying by office, role, skill set, and experience, with a standard benefits package available.