Mid-Level Data Engineer
ECS Corporate Services, LLC
Fairfax, United States of America
2 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
Intermediate Compensation
$ 98KJob location
Remote
Fairfax, United States of America
Tech stack
Azure
Data as a Services
Data Validation
ETL
Relational Databases
Database Queries
Python
Machine Learning
Microsoft Software
SQL Azure
NumPy
Performance Tuning
TensorFlow
Azure
Azure
Systems Integration
Unstructured Data
Data Logging
Azure
PyTorch
Pandas
Microsoft Fabric
Scikit Learn
Data Pipelines
Web Api
Microservices
Job description
- Develop production-grade ETL workflows using Python and Microsoft-based frameworks.
- Ingest, transform, and validate structured and unstructured data.
- Implement schema enforcement, data validation, and quality checks.
- Support Azure Data Lake Storage, Azure SQL, and Azure-based data services.
- Design workflow orchestration using Azure Data Factory or Microsoft Fabric/Foundry.
- Build Python-based data services using Pandas, PyTorch, TensorFlow, and related libraries.
- Develop API endpoints and microservices to support analytics and ML platform interoperability.
- Implement logging, monitoring, performance tuning, and operational reliability.
- Collaborate with data scientists, analysts, architects, and governance teams.
- Apply data governance best practices for compliance, reproducibility, and auditability.
Salary Range: $90,000-$98,000
Requirements
- 3+ years of experience developing or supporting advanced statistical, machine learning, or data pipeline solutions.
- Proficiency in Python, including Pandas.
- Strong SQL skills and experience integrating relational database sources.
- Hands-on experience with Azure cloud environments.
- Experience with ETL development using Python and Microsoft technologies.
- Experience with data validation, schema enforcement, and quality assurance.
- Familiarity with open-source data processing libraries such as NumPy, scikit-learn, PyTorch, or TensorFlow.