Accenture Federal Services
Data Engineer
About this role
Accenture Federal Services seeks a Data Engineer to build and maintain scalable data pipelines, data models, and analytics platforms supporting federal government missions. This entry-level role combines ETL development, data modeling, and cloud platform work in a collaborative Agile environment.
What you'll do
- Design, build, test, and maintain scalable data ingestion and transformation pipelines
- Support ETL/ELT activities to move data from source systems to analytics environments
- Assist in designing data models, schemas, and metadata for analytics and machine learning
- Perform data validation, profiling, quality checks, and implement governance best practices
- Deploy and optimize data assets on cloud platforms (Azure, AWS, or GCP)
- Partner with analysts and data scientists to understand requirements and participate in Agile ceremonies
What they're looking for
- SQL
- Python
- ETL pipeline development
- Data modeling and database design
- Cloud platforms (Azure, AWS, GCP)
- Data visualization
- Data quality and governance
- Agile/Scrum
Benefits
- Career development through hands-on experience and certifications
- Industry training and learning opportunities
- Collaborative and inclusive workplace culture
- Glassdoor Top 100 Best Place to Work recognition
- Comprehensive benefits package
- Work on impactful federal government projects
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Accenture Federal Services
Accenture Federal Services builds and maintains mission-critical technology solutions for the U.S. federal government, including cloud infrastructure, enterprise systems integrations, and cyber defense tools. The company is hiring DevOps engineers, full-stack developers, SAP specialists, and test engineers to support classified and unclassified federal government projects.
- Website
- accenturefederal.com
Likely interview questions
- Walk us through a data pipeline you've built—what tools did you use and what challenges did you encounter?
- How do you approach data quality validation and what methods have you used to identify data issues?