Design and lead AI/ ML and analytics solutions using best-in-class tools and platforms. Translate business challenges into actionable use cases and scalable data and AI products and services. Translate complex business challenges into actionable AI/ ML and data solutions using platforms such as Snowflake, Databricks, Azure, AWS, and GCP. Lead client engagements from strategy through implementation, ensuring delivery excellence and measurable outcomes. Mentor and lead multidisciplinary teams including scientists, engineers, and consultants. Lead data warehouse and or lakehouse initiatives, including requirements definition, architecture, modeling, implementation, and production readiness. Design and implement scalable data warehouse patterns, including dimensional modeling (star/snowflake), curated data marts, semantic layers, and governed self-service analytics. Direct development of ETL/ ELT pipelines, orchestration, and automation using modern tooling and engineering practices. Establish and mature data operationalization capabilities (e.g., performance tuning and cost optimization, release management and incident support processes, data quality rules and monitoring). Partner with client stakeholders to align warehousing work with data governance practices, access controls, and operational support models. What You Will Need:Bachelor’s degree from an accredited college/university. Based on our contractual obligations, candidate must be located within the United States and US Citizen. Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST". Minimum FIVE (5) years of experience delivering technical solutions and programs to public sector organizations. Experience in data and AI system development, with a proven ability to design scalable architectures and implement reliable models. Demonstrated experience leading data warehouse design and implementation, including data modeling, ingestion patterns, and production operations/ Strong knowledge of data warehousing concepts (e.g., dimensional modeling, analytics-ready data structures, CDC patterns, performance tuning, and cost controls for cloud platforms). Experience defining and implementing operating models for data platforms, including support processes, SLAs, monitoring, and continuous improvement. The knowledge and interest to remain current on emerging trends and techniques in the fields of data science and Artificial Intelligence. Strong communication skills to bridge technical and business worlds. During peak periods, 50% travel to north east client site, ie. during requirements gathering, UAT, implementation/go live, etc. What Would Be Nice To Have:Experience with ML - Ops and CI/ CD pipelines for AI/ ML deployment. Experience implementing cloud data warehouse and lakehouse solutions using Snowflake and or Databricks, including security, governance, and performance optimization. Demonstrated work experience within the public sector. Familiarity with data privacy regulations (GDPR, CCPA) and ethical AI frameworks. Advanced Degree (Master’s or PhD.) in Data Science, Computer Science, AI, or related field. Experience with API development and integration for data services. Experience supporting business development including RFP/ RFQ/ RFI responses involving data science / analytics.