Everforth ECS Federal is seeking a Senior Data Engineer-Advanced Data Integration & Cloud Solutions to work remotely.
The Senior Data Engineer will lead the design, build, and optimize scalable data pipelines and services that power advanced analytics and machine learning solutions. This role emphasizes data quality, performance, and interoperability in modern cloud environments, enabling CPSC’s strategic acceleration toward Sentinel-driven product safety analytics. The engineer will ensure secure, efficient, and reproducible data workflows that support predictive modeling, real-time monitoring, and actionable insights.
Key Responsibilities:
- Data Pipeline Engineering
- Develop production-grade ETL workflows using Python and Microsoft-based frameworks to ingest, transform, and validate large-scale structured and unstructured data.
- Implement schema enforcement, data validation, and quality checks to maintain integrity across diverse sources.
- Optimize pipelines for performance, scalability, and fault tolerance using open-source and cloud-native patterns.
- Cloud Integration & Orchestration
- Architect and manage Azure-based data solutions, including Data Lake Storage, Azure SQL, and cloud storage access from Python services.
- Design and deploy workflow orchestration using Azure Data Factory or Foundry for scheduling, monitoring, and automation.
- Ensure secure integration of APIs and services within the Microsoft ecosystem for seamless data exchange.
- Advanced Technical Development
- Build Python-based data services leveraging libraries such as Pandas, Pytorch, and other open-source frameworks for high-performance processing.
- Implement logging, monitoring, and performance tuning for robust operational reliability.
- Develop API endpoints and microservices to enable interoperability with analytics and ML platforms.
- Collaboration & Governance
- Work closely with data scientists, analysts, and cloud architects to deliver clean, reliable data for predictive modeling and real-time dashboards.
- Apply data governance best practices, ensuring compliance, reproducibility, and auditability across workflows.
- Contribute to Agile team processes, driving iterative improvements and shared problem-solving.
Salary Range: $130,000 - $150,000
General Description of Benefits
Preferred Qualifications- 5+ years developing and deploying advanced statistical and machine learning models or supporting data pipelines for such models.
- Proficiency in Python (Pandas required; scikit-learn, NumPy, and related libraries preferred).
- Strong SQL skills and experience integrating data from relational databases.
- Hands-on experience in cloud environments (Azure); Microsoft Data Engineer certification advantageous.
- Open-source frameworks for production-grade data pipelines.
- ETL development using Python and Microsoft technologies.
- Data validation, schema enforcement, and quality assurance.
- API development within Microsoft ecosystem.
- Performance optimization, logging, and monitoring for large-scale systems.
- Azure Data Lake Storage integration and Azure SQL connectivity.
- Workflow orchestration with Azure Data Factory.
- Deployment and operation of Python-based data services in Azure.
- Familiarity with open-source data processing libraries (Pandas, PyTorch, Tensorflow etc.).
Skills Required
- 5+ years developing and deploying advanced statistical and machine learning models or supporting data pipelines for such models
- Proficiency in Python, including required Pandas experience
- Strong SQL skills and experience integrating relational database data
- Hands-on experience with Azure cloud environments
- Microsoft Data Engineer certification
- Experience with open-source frameworks for production-grade data pipelines
- Experience developing ETL workflows using Python and Microsoft technologies
- Experience with data validation, schema enforcement, and quality assurance
- Experience developing APIs within the Microsoft ecosystem
- Experience with performance optimization, logging, and monitoring for large-scale systems
- Experience integrating Azure Data Lake Storage and Azure SQL
- Experience orchestrating workflows with Azure Data Factory
- Experience deploying and operating Python-based data services in Azure
- Familiarity with open-source data processing libraries such as Pandas, PyTorch, and TensorFlow
ECS Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ECS and has not been reviewed or approved by ECS.
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Healthcare Strength — ECS advertises multiple national-network medical plan options with HSA eligibility alongside dental and vision coverage. Coverage generally begins quickly and is paired with company-paid short- and long-term disability, adding stability to the health package.
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Retirement Support — A 401(k) with Safe Harbor and immediate vesting on employer contributions is emphasized, with an employer match available. Access to an employee stock purchase plan via the parent company provides an additional savings avenue.
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Parental & Family Support — Paid parental leave up to 30 days, adoption assistance, and other family-oriented leaves are highlighted. Feedback suggests these offerings add meaningful value beyond base pay for many roles.
ECS Insights
What We Do
ECS, a segment of ASGN (NYSE: ASGN), delivers advanced solutions and services in cloud, cybersecurity, artificial intelligence (AI), machine learning (ML), application and IT modernization, and science and engineering. The company solves critical, complex challenges for customers across the U.S. public sector, defense, intelligence and commercial industries. ECS maintains partnerships with leading cloud, cybersecurity, and AI/ML providers and holds specialized certifications in their technologies. Headquartered in Fairfax, Virginia, ECS has more than 3,400 employees throughout the U.S. and has been recognized as a Top Workplace by The Washington Post for the last five years.
