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Position Summary

ANSER is seeking a Data Engineer to design, build, and optimize enterprise-level data management systems to support Object-Based Intelligence (OBI) analytic processes and mission requirements. You will focus on integrating and maintaining scalable, secure data pipelines and architectures that enable advanced analytic workflows, visualization, and automation.

Day-to-Day Responsibilities

• Manage complex, long-term projects involving the design, development, integration, and installation of new information systems, databases, and data services.
• Perform technical studies, systems analysis, and feasibility assessments to ensure designs meet user requirements and define specifications for new or existing data and content management solutions.
• Design, develop, integrate, install, and optimize data management capabilities, data integration solutions, and both relational and non-relational databases (e.g., PostgreSQL) to support enterprise ingestion, storage, retrieval, and analytics.
• Collaborate with team members to design, refine, implement, and maintain resilient, scalable ETL pipelines using industry-standard tools and frameworks (e.g., Apache NiFi).
• Ensure ETL pipelines support secure data acquisition, normalization, enrichment, and delivery while meeting security controls, SLA requirements, and evolving data architecture needs.
• Collaborate with team members to design, implement, and maintain GraphQL APIs enabling flexible, efficient access and aggregation of data across distributed enterprise sources.
• Conduct testing and promote the integration of new databases and data services within existing IT infrastructure, including operational readiness testing and transitional user support.
• Create, execute, and document comprehensive test plans covering component, integration, system, compatibility/interface, user acceptance, and performance/stress testing.
• Monitor, maintain, and upgrade data services, content management systems, and databases; analyze system and database reports to ensure optimal performance.
• Identify data redundancy and design solutions to integrate or consolidate sources, reducing storage and maintenance costs while improving enterprise consistency.
• Produce technical data, performance reporting, and analysis outlining the operational characteristics of databases and data services across the DIA/DIE infrastructure.
• Develop and maintain disaster recovery and continuity plans to ensure data availability, access reliability, and database integrity during crisis situations.
• Analyze, evaluate, and provide recommendations, artifacts, and integration patterns for current, planned, and emerging data service, data management, and database technologies based on performance, cost, and security requirements.
• Design, develop, test, and implement unstructured data management solutions, including content extraction, tagging, data integration, web services, service versioning, containerization (e.g., Docker, Kubernetes), and infrastructure-as-code automation.
• Troubleshoot service, database, and user interface failures; implement temporary fixes and permanent corrections; interface with vendors, developers, and users; manage change requests; support code repositories; and prepare and present technical briefings to senior leadership.

Required Qualifications

• TS/SCI with Poly Clearance
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical discipline.
• Eight (8) or more years of experience in data engineering.
• Proven experience developing and managing data pipelines, ETL processes, and database systems for large-scale or mission-critical environments.
• Proficiency in Python, R, and SQL, and experience with data visualization tools such as Power BI or Tableau.
• Experience with data orchestration and automation tools (e.g., Apache NiFi, Airflow, or similar).
• Familiarity with knowledge graphs, semantic data modeling, and query languages (e.g., SPARQL, GraphQL).
• Experience developing, implementing, and evaluating AI/ML models for analytic efficiency and tradecraft compliance.
• Strong understanding of data security, access control, and system hardening in accordance with DoD and IC standards.
• Demonstrated ability to apply semantic data modeling and metadata standards within an OBI or analytic environment.
• Proficiency in containerization and orchestration technologies such as Docker and Kubernetes.

Preferred Qualifications

• Master's degree in Data Science, Computer Engineering, or related field.
• Familiarity with semantic web technologies (RDF, OWL, SPARQL) and their use in OBI data integration.
• Understanding of advanced analytic method augmentation.
• Experience developing data visualization and analytic tools supporting structured and unstructured intelligence data.
• Certification in Data Management or Cloud Architecture (e.g., AWS Certified Data Engineer, Google Professional Data Engineer).
• Ability to communicate technical data management concepts clearly to both technical and non-technical audiences.
• Experience supporting DIA, IC, or DoD analytic modernization or OBI initiatives.
• Experience with distributed data processing, cloud-based analytics, or large-scale machine learning architectures.
• Experience working with in support of Defense Intelligence All-source Analytic Enterprise (DIAAE) OBI efforts, the Defense Intelligence Enterprise Knowledge Model (DIEKM), and Defense Intelligence Core Ontology (DICO).
• Experience developing OBI governance and tradecraft to assist DIA and other DIAAE organizations conducting OBI.