> Markdown version of [/jobs/ext/4717826-cleared-data-engineer](https://www.wearedevelopers.com/jobs/ext/4717826-cleared-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Cleared Data Engineer

- **Company:** Guidehouse Inc.
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Salary:** $85,000 - $141,000
- **Contract:** Permanent contract
- **Skills:** Computer Programming, Data Dictionary, Information Engineering, Extract Transform Load (ETL), Python (Programming Language), Metadata, Standard Sql, SQL Databases, Data Streaming, Data Classification, Pyspark, Information Technology, Low Latency, Data Pipelines, Databricks
- **Published:** November 14, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9313976/cleared-data-engineer

## About the Role

* An ACTIVE and CURRENT SECRET federal security clearance
 * Bachelor's degree
 * SIX (6) years of total experience in a data or programming discipline, including THREE (3) years of experience in data engineering
 * Proficiency in data engineering-related programming languages such as Python, PySpark, and/or SQL
 * Experience with scheduling, monitoring, troubleshooting, and optimizing production ETL/ELT pipelines
 * Experience with data engineering principles and best practices
 * Excellent problem-solving skills and attention to detail
 * Selected Candidate must be able to commute to client and Guidehouse offices as needed

What Would Be Nice To Have :

 * Master's degree in computer science or related field
 * Experience working with system and application logs
 * Familiarity with the Databricks platform
 * Strong communication and collaboration skills, with the ability to work effectively in a team environment

## Description

* Design, develop, test, deploy, and maintain scalable batch and streaming data pipelines in Databricks using Python, PySpark, SQL, and reusable engineering patterns.
 * Transform raw source data into curated, analysis-ready datasets and dimensional models that support cybersecurity metrics, risk analysis, dashboards, and executive reporting.
 * Develop automated data-quality controls for ETL jobs, including schema, completeness, validity, consistency, uniqueness, timeliness, referential-integrity, and source-to-target reconciliation checks.
 * Define appropriate handling for failed quality checks, including quarantining invalid records, stopping critical loads, generating alerts, documenting exceptions, and coordinating corrective action with data owners.
 * Schedule and orchestrate production workflows; monitor job status, freshness, throughput, latency, resource utilization, and failures; troubleshoot root causes; and restore processing within agreed service levels.
 * Optimize pipeline reliability, performance, and cost through efficient transformations, workload configuration, incremental processing, partitioning, and compute-resource management.
 * Implement and maintain data-governance and quality-assurance standards, including access controls, metadata, data classification, ownership, lineage, retention, auditability, and protection of sensitive cybersecurity information.
 * Maintain source-to-target mappings, data dictionaries, transformation rules, validation evidence, standard operating procedures, runbooks, and other technical documentation needed for operations, knowledge transfer, and audit readiness.
 * Partner with cybersecurity analysts, data owners, system administrators, dashboard developers, and business stakeholders to define data requirements, metrics, thresholds, and acceptance criteria.
 * Maintain effective working relationships with client management and staff, anticipate stakeholder needs, communicate delivery risks and dependencies, and resolve issues in a timely and professional manner.
 * Organize and lead client meetings by coordinating schedules, developing and distributing agendas and pre-read materials, facilitating discussions and decisions, recording minutes, maintaining required documentation, and tracking action items through closure.
 * Participate in peer reviews, testing, release activities, and continuous-improvement efforts to strengthen engineering practices, reduce recurring defects, and improve the reliability and usability of data products.