Join our data engineering team to build robust, scalable data infrastructure that powers AI/ML initiatives and business intelligence across commercial and government clients. This role focuses on designing and implementing modern data architectures, pipelines, and platforms.
Key Responsibilities- Design and implement scalable data architectures using modern data stack technologies
- Build real-time and batch data processing pipelines using Apache Spark, Kafka, and Airflow
- Develop ETL/ELT processes for data integration across multiple source systems
- Implement data lake and data warehouse solutions using Snowflake, Databricks, and cloud services
- Build and maintain cloud-based data platforms on AWS, Azure, and GCP
- Design data mesh architectures and self-service analytics platforms
- Optimize data storage, processing, and query performance
- Implement data quality monitoring and validation frameworks
- Design data cataloging and metadata management solutions
- Ensure data security, privacy, and compliance with federal regulations
- Develop data lineage tracking and impact analysis capabilities
- Bachelor's degree in Computer Science, Engineering, or related field
- 5+ years of data engineering experience in enterprise environments
- 3+ years of cloud data platform experience
- Programming: Advanced Python, SQL, Scala; familiarity with Java
- Data mesh and modern data architecture experience
- Terraform, CloudFormation, or similar IaC experience