Data Engineering SME

Doist

Herndon (VA)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Platinum Technologies is seeking a Data Engineering Subject Matter Expert (SME) to lead the design, implementation, and optimization of enterprise data architectures that support Object-Based Intelligence mission requirements. This role requires an active TS/SCI with CI polygraph and citizenship.

You will drive scalable data pipelines, ontologies, knowledge graphs, and Semantic Web technologies while collaborating across ontology engineers, software engineers, and Government stakeholders to

Qualifications

  • Requires U.S. citizenship and active TS/SCI with CI polygraph.
  • 12+ years of experience with advanced degree or 17+ years with a bachelor’s.
  • Experience designing enterprise-scale data engineering and data integration architectures.
  • Experience developing ETL/ELT pipelines with modern data tools.
  • Experience integrating structured, semi-structured, and unstructured data.
  • Experience with relational, NoSQL, and graph databases; distributed processing.
  • Knowledge of data modeling, metadata management, governance, and architecture.
  • Familiarity with Semantic Web technologies and ontology-based data integration.
  • Experience with cloud-based or containerized data platforms including Kubernetes/OpenShift.
  • Strong communication of complex concepts to technical and non-technical stakeholders.

Responsibilities

  • Lead design and implementation of enterprise data engineering solutions for OBI mission requirements.
  • Design and optimize scalable data pipelines for ingesting, transforming, validating, and integrating data from multiple sources.
  • Develop data integration frameworks supporting ontologies, knowledge graphs, RDF/OWL/SPARQL.
  • Collaborate with engineers, analysts, and Government stakeholders to translate requirements into scalable solutions.
  • Design data architectures supporting cloud-native, distributed, and hybrid environments.
  • Establish data quality, metadata, lineage, and governance processes across assets.
  • Optimize processing performance with modern distributed frameworks and storage technologies.
  • Support AI/ML initiatives by providing curated datasets with semantic context for training and inference.
  • Develop monitoring, validation, and testing capabilities to ensure data accuracy and reliability.
  • Produce technical docs, data flow diagrams, and interface specifications.

Skills

Enterprise data engineering
ETL/ELT pipelines
Data integration architectures
Data modeling
Metadata management
Data governance
Cloud environments
Communication to stakeholders

Education

Advanced degree
Bachelor's degree + 17 years experience

Tools

Kubernetes
OpenShift
Relational databases
NoSQL databases
Graph databases
Distributed processing frameworks

Job description

Who we are. Platinum Technologies is a Northern Virginia based integrated solutions firm that specializes in Cybersecurity, Cloud and Digital Services to the Public Sector. Our team solves hard problems and helps our Mission Partners achieve their goals. If you are self-motivated, possess demonstrated learning agility, and are passionate about delivering high-quality work products - we want to hear from you. We lead with technical expertise, but that is just the tip of the iceberg - the 'Why' matters. At Platinum, we don't hire people to do a job. We provide professional and leadership development to complement our self-motivated domain experts. Our teammates are dot-connecting leaders that operate in a mutually accountable environment to deliver thought leadership, expert technical analysis, and quality execution for our clients. This position requires an active U.S. Government Security Clearance at the TS/SCI level with CI polygraph. You.

Data Engineering Subject Matter Expert (SME)

Platinum Technologies is seeking a Data Engineering Subject Matter Expert (SME) to join our team. In this position you will provide technical leadership for the design, implementation, and optimization of enterprise data engineering solutions supporting Object-Based Intelligence (OBI) mission requirements, ontology-driven data integration, and advanced analytics.

The Data Engineering Subject Matter Expert serves as the senior technical authority for developing and implementing scalable data architectures, pipelines, and integration frameworks that enable the ingestion, transformation, management, and delivery of structured, semi-structured, and unstructured data.

This position applies data engineering best practices to support enterprise ontologies, knowledge graphs, Semantic Web technologies, and AI/ML applications while ensuring data quality, governance, interoperability, and security across diverse mission systems.

Working closely with ontology engineers, software engineers, database engineers, data scientists, and Government stakeholders, the Data Engineering SME develops modern data solutions that support mission analytics, knowledge discovery, and decision advantage.

What you get to do
  • Lead the design, development, and implementation of enterprise data engineering solutions supporting Object-Based Intelligence mission requirements.
  • Design and optimize scalable data pipelines for ingesting, transforming, validating, and integrating data from multiple internal and external sources.
  • Develop data integration frameworks that support enterprise ontologies, knowledge graphs, and Semantic Web technologies, including RDF, OWL, and SPARQL.
  • Collaborate with ontology engineers, software engineers, database engineers, analysts, and Government stakeholders to translate mission requirements into scalable data engineering solutions.
  • Design and implement data architectures supporting cloud-native, distributed, and hybrid computing environments.
  • Establish data quality, metadata management, lineage, and governance processes to ensure consistency, traceability, and interoperability across enterprise data assets.
  • Optimize data processing performance using modern distributed processing frameworks and scalable storage technologies.
  • Support AI/ML initiatives by developing reliable, high-quality data pipelines that provide curated datasets and semantic context for model training, inference, and decision support.
  • Develop automated monitoring, validation, and testing capabilities to ensure data accuracy, completeness, and operational reliability.
  • Produce and maintain technical documentation, data flow diagrams, interface specifications, data dictionaries, and engineering standards.
  • Provide technical leadership, mentoring, and knowledge transfer activities to Government personnel and project team members regarding data engineering best practices, modern data architectures, and enterprise integration strategies.
Required Skills
  • Must be a U.S. citizen and have an active TS/SCI with CI polygraph.
  • Minimum twelve (12) years of experience and an advanced degree or 17 years of experience with a bachelor's degree.
  • Demonstrated experience designing and implementing enterprise-scale data engineering solutions and data integration architectures.
  • Experience developing ETL/ELT pipelines using modern data engineering tools and frameworks.
  • Experience integrating structured, semi-structured, and unstructured data from heterogeneous enterprise data sources.
  • Experience with relational databases, NoSQL databases, graph databases, and distributed data processing platforms.
  • Knowledge of data modeling, metadata management, data governance, and enterprise data architecture principles.
  • Familiarity with Semantic Web technologies, knowledge graphs, or ontology-based data integration.
  • Experience supporting cloud-based or containerized data platforms, including Kubernetes and OpenShift.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.

The Company is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, sexual orientation/gender identity, age, or genetic information.

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