Data Engineer

Analytic Services Inc•Reston, VA

About The Position

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.

Requirements

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.

Nice To Haves

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.

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.