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# Senior Data Engineer

- **Company:** Kentro LLC
- **Location:** Fayetteville, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Geographic Information Systems, Application Programming Interfaces (APIs), Airflow, Cloud Computing, Information Systems, Databases, Continuous Integration, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Relational Databases, Database Development, Distributed Computing Environment, Elasticsearch, Graph Database, Python (Programming Language), Linux System Administration, Machine Learning, Meta-Data Management, Microsoft SQL Server, Object-Oriented Software Development, Performance Tuning, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Transact-SQL, Unstructured Data, Management of Software Versions, Enterprise Data Management, Palantir Foundry, Apache Spark, Git, Pyspark, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Deployment Automation, Apache Kafka, Apache Nifi, Operational Systems, Data Management, Software Version Control, Data Pipelines, Automation Anywhere, OpenSearch, Docker, Databricks
- **Published:** November 3, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9284839/senior-data-engineer

## About the Role

* Education: Bachelor's degree in computer science, data science, information systems, or a related technical field, plus 7 years of relevant experience. 8140 compliances in certification/training may substitute for a degree.
 * Training: Meets DoD 8140 foundational and residential qualification requirements for the assigned work role (approved certification, education, or training) Trainings include:
 + SecurityX / CASP+
 + CCSP
 + Cloud+
 + CSC
 + GCLD
 + GCSA
 + GSEC
 * Experience: 7+ years of professional data engineering experience
 * Technical Skills:
 + Strong Python and SQL development skills, demonstrated through production pipelines or applications.
 + Experience with distributed data processing (PySpark / Apache Spark).
 + Experience with relational and non-relational data stores and with data modeling and schema design.
 + Experience integrating multiple source systems into a centralized data platform.
 + Proficiency in Linux environments, Git, and CI/CD workflows.
 + Working knowledge of data governance, data lineage, and metadata management.

Preferred Qualifications:

 * Hands-on experience with Microsoft SQL Server (MSS), including T-SQL development and performance tuning.
 * Prior work for USASOC, USSOCOM, or another special operations or Army component.
 * Experience building and operating data platforms in classified or air-gapped environments (JWICS, SIPRNet).
 * Experience with a modern data platform such as Palantir Foundry, Databricks, or comparable (pipelines, ontology/object modeling, application building).
 * Experience with pipeline orchestration and streaming tools (e.g., Airflow, NiFi, Kafka).
 * Experience with Elasticsearch/OpenSearch, graph databases, or geospatial data.
 * Experience with containers and orchestration (Docker, Kubernetes) and infrastructure as code.
 * Experience deploying ML/AI models or analytics into operational systems.
 * Familiarity with RMF, ATO processes, and secure software development practices.
 * Cloud experience in classified or government cloud environments.

Clearance Requirement:

 * Active TS/SCI clearance
 * US Citizen

## Description

* Design, build, test, and maintain scalable batch and streaming data pipelines (ETL/ELT) in classified and air-gapped environments.
 * Develop transformation logic in Python, SQL, and PySpark to ingest, clean, normalize, and enrich structured and unstructured data.
 * Integrate data from mission systems, operational applications, databases, APIs, and file-based sources into enterprise data platforms.
 * Design data models, schemas, and entity relationships that support analytics, reporting, and downstream applications.
 * Build and publish curated datasets and data products with clear documentation, versioning, and service-level expectations.
 * Implement data quality checks, validation, monitoring, and alerting to ensure pipeline reliability and trusted outputs.
 * Establish and maintain data lineage, metadata, and cataloging in accordance with data governance policies.
 * Apply data security controls, including role-based and attribute-based access, data tagging and labeling, and need-to-know enforcement.
 * Automate deployment and operations using CI/CD, version control, and infrastructure-as-code practices.
 * Troubleshoot production issues, perform root cause analysis, and optimize pipeline performance and cost.
 * Support the deployment of analytics and ML/AI workflows into operational systems.
 * Collaborate with mission owners, analysts, data scientists, security staff, and system administrators to translate requirements into engineered solutions.