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# Data Engineer

- **Company:** Ivertix Incorporated
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Data Analysis, Confluence, JIRA, Microsoft Azure, Cloud Database, Code Review, Information Systems, Data Validation, Extract Transform Load (ETL), Relational Databases, Distributed Systems, Python (Programming Language), PostgreSQL, Microsoft SQL Server, Oracle (Applications), SQLAlchemy, Apache Spark, Pandas, Information Technology, Software Version Control, Data Pipelines, Databricks
- **Published:** September 17, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9171923/data-engineer

## About the Role

Bachelor's degree in computer science, Data Science, Information Systems, or related field.
2+ years of experience in data analysis or Python-based pipeline development.
Proficiency in Python (pandas, PyArrow, Requests, SQLAlchemy).
Experience writing and optimizing SQL queries with relational databases (PostgreSQL, SQL Server, Oracle).
Working knowledge of ETL/ELT, data modeling, and schema design.
Exposure to cloud or hybrid environments (AWS, Azure, or similar).
Strong communication and teamwork skills in remote, distributed environments (Jira, Confluence, Teams, Slack).

## Description

Develop, optimize, and maintain Python-based data pipelines for ingestion, transformation, and movement of data from multiple sources.
Implement and monitor ETL/ELT workflows using modern frameworks (Databricks, Spark, and cloud data services).
Integrate and validate datasets within Advana and related DoD environments, ensuring accuracy, consistency, and performance.
Translate business and technical requirements into reusable, scalable data solutions that support enterprise analytics.
Conduct data quality checks, root-cause analysis, and resolution of pipeline or integration issues.
Maintain documentation for data pipelines, schemas, and transformation logic.
Participate in Agile ceremonies, code reviews, and version control practices following engineering best standards.