Data Engineer

Build, optimize, and maintain batch and real-time data ingestion pipelines, including ETL/ELT processes for structured and unstructured data
Lead design and implementation of scalable ETL processes across complex, distributed systems
Develop and manage data lake architecture for structured and unstructured data
Use dbt, Informatica, Azure Data Factory, Databricks, AWS Glue, AWS Event Bridge, and S3 Event Notifications for data transformation, workflow automation, orchestration, and scheduling
Write performant SQL queries and Python/JavaScript scripts for data parsing, ingestion, and cleanup
Conduct data profiling, linkage, validation, and quality checks across diverse sources
Ensure data quality, lineage, governance, and compliance across systems
Enable cloud-based data processing using AWS S3 and Azure Blob and support API integration
Collaborate with data science, engineering, and stakeholder teams to deliver data products and support reporting and model development
Mentor junior engineers and provide technical guidance and peer reviews
Maintain technical documentation for pipelines, data structures, infrastructure, standards, and data product specifications
Support secure data governance practices and performance tuning in modern cloud platforms

• Must be a U.S. Citizen
• Bachelor's degree in Computer Science or a related field, with a minimum of three (3) years of relevant work experience
• An active security clearance, or the ability to obtain one, is required
• Strong proficiency in Python and SQL
• Hands-on experience with Pandas, PySpark, and AWS Glue
• Deep understanding of ETL frameworks, data lake design, and cloud-based architecture
• Familiarity with real-time and batch data processing tools and methodologies
• Experience with data governance, security compliance, and maintaining data quality standards
• Must be local to the Vienna, VA area and able to work on-site at the Vienna, VA office (3-5 days/week); hybrid arrangements available at supervisors' discretion

Demonstrates expertise in building and optimizing ETL processes, managing data lake architecture, and ensuring data quality and compliance in cloud environments. Proficient in Python and SQL, with hands-on experience in data transformation tools and methodologies.

• ETL Frameworks
• Data Lake Design
• Python Programming
• SQL Proficiency
• Data Governance

• ETL Processes
• Data Ingestion
• Data Transformation
• SQL Queries
• Python Scripting
• Data Profiling
• Data Quality Checks
• Cloud-Based Architecture
• Real-Time Data Processing
• Batch Data Processing

• Mentoring
• Collaboration
• Technical Guidance

• Active Security Clearance

• Data Governance
• Data Quality Standards
• Cloud Platforms
• Data Compliance
• Data Architecture

• Dbt
• Informatica
• Azure Data Factory
• Databricks
• AWS Glue
• AWS Event Bridge
• S3 Event Notifications
• Pandas
• Py Spark
• Azure Blob