Data Engineer
$61,900–$141,000 year
On-siteDayton, Ohio, United States
Job Summary
Develop and deploy pipelines and platforms that organize disparate data into meaningful structures for mission-driven clients. Build advanced technology solutions involving data acquisition, preparation, database architecture, and governance while supporting the assessment, design, and maintenance of scalable data lakes and warehouses. Integrate AI/ML capabilities into production workflows and implement monitoring tools to maintain data integrity and fix broken pipelines. Collaborate within a multi-disciplinary team of analysts, engineers, and developers to assess, design, and develop these scalable platforms.
Required Qualifications
- 5+ years of experience with data architecture, design, or engineering projects
- Experience with cloud migration and modernization efforts and creating automated Extract, Transform, Load (ETL) processes to move data from unstructured source data to application governed storage
- Experience with the data pipelines, including data acquisition, data prep, database architecture, data governance, and data tagging
- Experience with non-relational NoSQL, semi-relational databases, and relational SQL databases
- Experience with implementing monitoring tools to maintain data integrity, fix broken pipelines, and handle missing or corrupt information and designing scalable data lake, warehouse, and analytics solutions
- Experience integrating AI/ML capabilities into production workflows or operator tooling, such as LLM enabled assistants, model augmented decision aids, or automation solutions
- Knowledge of AWS services, such as S3, IAM, EventBridge, Step Functions, or Lambda
- Ability to work both within a team and independently to manage tasks with minimal supervision
- TS/SCI clearance
- Bachelor's degree in Computer Science or technical discipline
Desired Qualifications
- Experience evaluating data analytic or science technologies and platforms
- Experience designing cloud-native data platforms in AWS
- Experience with Cloud Architecture and evaluating and selecting cloud analytics architectures
- Experience with Data Marts and Data Warehouses and creating, managing, and troubleshooting complex operational data flows
- Experience with ETL tools, such as dbt and Airflow
- Experience with Source code management and integration such as GitHub
- Experience with CI/CD practices
- Experience with programming languages such as Python, Rust, C++, Java, etc.
- Experience with API development
- AWS architecture
- Certifications such as Solution Architect Certification
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