Groundswell is looking to solve complex challenges facing federal agencies by designing, building, and deploying AI-driven and data-centric enterprise applications.
Requirements
- 5+ years of data engineering or full-stack development experience.
- Strong experience with SQL and one or more programming languages (Python, Java, Scala).
- ETL Development: Experience with frameworks such as Apache Airflow, AWS Glue, etc.
- Cloud Platforms: Hands-on experience with AWS, Azure, or GCP.
- Data Analysis & Validation: Implementing data quality frameworks and validation processes.
- Programming: Strong SQL plus proficiency in Python, Java, or Scala.
- Experience with LLM data requirements, vector databases, and/or AI model deployment.
Responsibilities
- Design, develop, and maintain ETL/ELT pipelines to support data ingestion from multiple sources.
- Seamlessly onboard and integrate new data sources into existing pipelines.
- Build automated data validation frameworks to ensure accuracy and consistency.
- Optimize data pipelines for performance, scalability, and cost efficiency.
- Implement data quality monitoring, alerting systems, and lineage tracking.
- Architect solutions across AWS, Azure, and GCP to support federal client needs.
- Build pipelines to support Large Language Model (LLM) training and inference workflows.
Other
- This is a mid-level, customer-facing engineering role.
- This is a hybrid role and requires being onsite in the Mclean office and/or client site 3 days/week.
- Demonstrated leadership in guiding engineering teams.
- Strong communication, collaboration, and problem-solving skills.
- Must be able to obtain and maintain a federal government security clearance. US citizenship required for clearance purposes.
