Develop and maintain metadata-driven data pipelines for ingestion, transformation, and delivery of data
Build and support ETL/ELT processes for both legacy and modern data sources
Implement data transformations to convert legacy formats (e.g., SFTP, flat files) into modern formats (e.g., XML, JSON, APIs)
Develop API integrations and data services supporting real-time and near real-time data exchange
Support implementation of data quality checks, validation rules, and monitoring processes
Collaborate with a Data Architect to implement data models, schemas, and integration patterns
Optimize pipelines and queries for performance, scalability, and reliability
Assist in documenting data flows, interfaces, and pipeline configurations
Support DevSecOps practices to ensure a standardized data environment, including implementing CI/CD pipelines, automated testing, and deployment
Work in cross-functional team with data scientists, data engineers, and business stakeholders

Experience developing and maintaining ETL pipelines and data integration workflows
Strong proficiency in SQL and Python
Experience with cloud platforms (AWS, Azure, GCP, GovCloud) and cloud-native architectures
Hands-on experience with cloud-based data warehouses and object storage (S3, Redshift, Snowflake)
Experience with API integration and data exchange
Understanding of database design principles, data modeling, schema development, and data-centric documentation
Experience integrating data from a variety of data source types
Experience improving code performance and query optimization
Outstanding problem-solving skills
Excellent verbal and written communication skills
4+ years of experience as a Data Engineer or similar role
Bachelor’s degree in Computer Science, Mathematics, or comparable academic discipline
Must have or be willing to obtain Secret Clearance (this requires US Citizenship)

Data Engineer

Key skills