Senior Data Engineer-TS/SCI

MetaPhase Consulting•Washington, DC

1d•Hybrid

About The Position

MetaPhase supports a secure Federal mission environment that uses advanced visual analytics to integrate, analyze, and act on information from multiple data sources. The work combines data engineering, cloud infrastructure, analytics, and application delivery to provide reliable information to mission users. MetaPhase is seeking a Senior Data Engineer with at least 10 years of relevant experience to design, build, and sustain scalable data pipelines, enterprise data stores, and analytic data products. This engineer will convert structured, semi-structured, and unstructured data into governed, high-performing information assets that support visual analytics, investigative workflows, and operational decision making.

Requirements

Minimum of 10 years of relevant experience in data engineering, data architecture, data integration, or a closely related technical discipline.
Bachelor’s degree in computer science, data science, information systems, engineering, mathematics, or a related field.
Active Top Secret clearance with eligibility for SCI access.
U.S. Citizenship is required.
Advanced proficiency in Python, SQL, and database development, with hands-on experience designing relational data stores and optimizing data-processing performance.
Experience building and operating ETL or ELT pipelines, including batch and streaming data processing, data validation, error handling, and monitoring.
Experience integrating diverse data sources and managing data quality, metadata, lineage, access controls, and security requirements in a Federal or similarly regulated environment.
Ability to communicate technical data concepts clearly and collaborate effectively with mission users, analysts, engineers, and delivery leadership.

Nice To Haves

Experience delivering data engineering capabilities for visual analytics, cyber, intelligence, law enforcement, or other mission-critical environments.
Experience with cloud data platforms and services in AWS, Azure, or comparable regulated environments.
Proficiency with PostgreSQL, OpenSearch or Elasticsearch, Apache Kafka, Apache NiFi, Cribl, Docker, Kubernetes, and infrastructure-as-code tools.
Experience building reusable data ingestion frameworks, schema-management patterns, and automated data-quality controls.
Experience with graph, geospatial, or large-scale entity-resolution data models and analytics.
Current TS/SCI clearance and demonstrated ability to support work in secure on-site environments.

Responsibilities

Design, develop, and optimize batch and real-time data pipelines that ingest, validate, transform, and publish structured, semi-structured, and unstructured data.
Build and maintain large-scale relational databases, cloud storage, and data models that support high-performance web and desktop visual analytic applications.
Develop ETL and ELT processes, data-quality checks, metadata, lineage, and monitoring that make complex data reliable and usable across the mission lifecycle.
Engineer scalable data services, APIs, and curated datasets that enable bulk analysis of relationships, advanced graphics, visualization, and high-performance computing workloads.
Optimize query performance, database structures, indexing, and data-processing workflows while integrating new sources with existing warehouse and analytic environments.
Collaborate directly with analysts, software engineers, architects, and mission users to refine data requirements, test delivered capabilities, and improve data products through iterative delivery.
Apply secure engineering practices for data access, auditability, configuration management, and operational resilience across open-source, COTS, and GOTS technologies.