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 EventBridge, 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 Requirements 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 Core Competencies 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. Highest-signal resume keywords ETL Frameworks Data Lake Design Python Programming SQL Proficiency Data Governance ATS Optimization Keywords Hard Skills 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 Soft Skills Mentoring Collaboration Technical Guidance Certifications & Qualifications Active Security Clearance Industry Keywords Data Governance Data Quality Standards Cloud Platforms Data Compliance Data Architecture Tools & Technologies Dbt Informatica Azure Data Factory Databricks AWS Glue AWS EventBridge S3 Event Notifications Pandas PySpark Azure Blob #J-18808-Ljbffr