US Citizen with the ability to secure a US public trust clearance
Bachelor's degree in computer science, IT, Data Science, Engineering, Mathematics, or related field
10+ years of IT experience in enterprise data architecture, AI/ML, data engineering, and management
5+ years of experience with AWS and/or Databricks data solutions
Proven expertise in Relational and Dimensional Data Modeling and Lakehouse architectures
Advanced proficiency in statistical, programming, and engineering methods for building DataOps and MLOps pipelines
Responsibilities
Lead and architect enterprise-wide data initiatives including integration, migration, and data warehouse builds
Develop and evaluate AI/ML solutions in AWS and Databricks
Apply advanced statistical and programming methods for data analysis
Lead data modeling across identity and biometrics domains
Establish and enforce a data governance framework for accuracy
Conduct cost-benefit analyses for technical and architectural options
Integrate AI/ML and data analytics into DevSecOps workflows
Maintain AI/ML models through CI/CD pipelines and optimize alternatives
Provide a continuous model validation framework
Support data analytics for program activities and recommend optimizations
Mentor Data Scientists and Engineers, collaborating on secure data handling
Benefits
Opportunity to work on high-impact projects in national security
Collaborative environment with a focus on mentorship and professional growth
Access to cutting-edge technologies and tools in data architecture and AI/ML
Potential for career advancement within a large enterprise
Engagement in meaningful work that supports law enforcement and public safety
Full Job Description
Analytica is looking for a Lead Data Architect to oversee, manage and provide hands-on implementation of enterprise data architecture, DataOps and MLOps for key client program centered around network and entity services. This leader designs and sustains data architectures and data pipelines that support identity and biometrics applications, integrates law-enforcement-sensitive data for screening and vetting, and leads for AI/ML practice spanning model development, deployment, and continuous validation on AWS and Databricks.
Key Responsibilities:
Lead and architect enterprise-wide initiatives including system integration, data migration, transformation, data warehouse build, data mart build, data lakes implementation and support, and O&M for a large enterprise.
Develop and evaluate production AI/ML solutions in AWS and Databricks.
Apply advanced proficiency in statistical, programming, and engineering methods for data analysis (e.g., SQL, Python, statistical modeling).
Lead Relational and Dimensional Data Modeling across identity and biometrics data domains.
Establish and enforce a data governance framework to improve accuracy using integrated internal and external disparate data sources.
Conduct cost-benefit analyses for competing technical and architectural options.
Integrate AI/ML, data analytics, and entity resolution into DevSecOps workflows and system architectures.
Maintain AI/ML models through user stories and the DevSecOps CI/CD pipeline, including optimization and evaluation of alternates.
Prefer open-source models; provide comparable analysis and justification when proprietary models are proposed.
Provide a continuous model validation framework to the extent possible.
Support data analytics on program and system activities, including assessment of performance and manual processes with automation/optimization recommendations.
Mentor Data Scientists, Data Engineers, and Database Management staff; collaborate with Architect Leads and ISSO personnel on secure handling of law-enforcement-sensitive data.
Required Experience & Qualifications:
US Citizen with the ability to secure a US public trust clearance
Bachelor's degree in computer science, Information Technology, Data Science, Engineering, Mathematics, or a related technical field
10+ years of IT experience, focusing on enterprise data architecture, AI/ML, data engineering, and data management.
5+ years of experience implementing AWS and/or Databricks data solutions
Significant experience with Python and Python
Proven Experience leading and architecting enterprise-wide initiatives spanning system integration, data migration, transformation, data warehouse/mart build, data lakes implementation and support, and O&M for a large enterprise.
Proven expertise in Relational and Dimensional Data Modeling and Lakehouse architectures
Advanced proficiency in statistical, programming, and/or engineering in building DataOPs and MLOPs pipelines for data analysis
Preferred Experience & Qualifications:
Databricks Professional or AWS Solution Architect or Data Engineer strongly preferred
Advanced degree (Master's or PhD) in Data Science, Statistics, Computer Science, Mathematics, or related quantitative discipline.
Experience with PyTorch, SciKit-Learn, NumPy, Spark/Scala, Kafka, and PostgreSQL.
Experience with Tableau and large-scale data visualization for executive and operational reporting.
Prior USCIS, DHS, or federal law enforcement / national security data program experience.
