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# Principal Database Engineer

- **Company:** ASRC Federal Holding Company
- **Location:** Washington, DC, United States
- **Experience:** Expert
- **Salary:** $135,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Databases, Data Architecture, Data Validation, Data Cleansing, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Systems, Document-Oriented Databases, Apache Hadoop, Python (Programming Language), Software Tools, SQL Databases, Data Ingestion, Apache Spark, Information Technology, Data Management, Data Pipelines
- **Published:** September 23, 2026
- **Apply:** https://www.dcjobsite.com/job.asp?id=3401621008&tx=ZT2625TTD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

Education: Minimum bachelor's degree in data science, statistics, computer science, engineering, mathematics, or a closely related discipline; an advanced degree (master's or doctorate) is preferred., * At least eight (8) years of experience in data science, advanced analytics, or a closely related field, with hands-on experience designing and implementing analytical solutions in operational settings.

 * Advanced proficiency in data engineering tools and technologies such as Python, SQL, and ETL processes.
 * Experience with cloud platforms and big data technologies (e.g., AWS, Azure, Hadoop, Spark).
 * Strong understanding of data modeling, data architecture, and database management principles.
 * Proven experience in data validation, data cleansing, and data quality assessment techniques.
 * Excellent analytical skills combined with the ability to think critically and solve complex problems.

Certifications/Clearance:

 * Relevant data engineering certifications (e.g., AWS Certified Data Engineer - Associate, Google Professional Data Engineer) are a plus

## Description

The Data Engineer will design, build, and maintain scalable data architectures and pipelines that support data quality improvement efforts under the ICE LESA Data Quality Improvement Support Services contract. This role is responsible for ensuring efficient ingestion, transformation, and management of data across multiple systems, collaborating closely with data scientists, analysts, and technical teams to enhance data accessibility and reliability. Key responsibilities include maintaining data integrity, conducting root cause analysis of data issues, and implementing solutions that streamline data processes and improve operational efficiency. Strong technical expertise and the ability to work effectively with cross-functional stakeholders are essential to ensure data solutions are delivered on time, within scope, and aligned with organizational standards., * Design, construct, test, and maintain scalable data pipelines and architectures to support data ingestion and transformation.

 * Collaborate with data scientists and analysts to implement data solutions that uncover insights and improve data quality.
 * Perform root cause analysis to identify data errors and propose solutions for remediation.
 * Continuously analyze and optimize data processes and systems for efficiency and performance.\
 * Validate and ensure the reliability of data through systematic testing and monitoring of data quality metrics.
 * Document data engineering processes, system workflows, and best practices for stakeholder reference.
 * Collaborate with Error Response Teams (ERTs) to support remediation of data quality issues.


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