Senior Data Engineer

Everforth ECS is seeking a Senior Data Engineer to work remotely. Please Note: This position is contingent upon contract award. Everforth ECS is seeking a Senior Data Engineer to lead the design, development, and optimization of scalable enterprise data pipelines and cloud-native data services supporting the U.S. Consumer Product Safety Commission (CPSC). This role will help modernize and stabilize CPSC's Azure-based data infrastructure while enabling advanced analytics, machine learning, and Sentinel-driven product safety initiatives., * Lead development of production-grade ETL workflows using Python and Microsoft-based technologies.

• Design and optimize scalable ingestion, transformation, and validation pipelines for structured and unstructured datasets.
• Implement schema enforcement, data validation, anomaly detection, and quality assurance frameworks.
• Architect and manage Azure-based data solutions including Azure Data Lake Storage and Azure SQL.
• Design and deploy orchestration workflows using Azure Data Factory and Microsoft Fabric/Foundry.
• Develop Python-based data services leveraging libraries such as Pandas, PyTorch, TensorFlow, and related open-source frameworks.
• Build APIs and microservices supporting interoperability with analytics and AI/ML platforms.
• Implement monitoring, logging, fault tolerance, and performance optimization for large-scale systems.
• Collaborate closely with data scientists, analysts, architects, and governance teams to deliver secure, reliable, and analytics-ready datasets.
• Support Agile development processes and contribute to continuous improvement initiatives.

• 5+ years of experience developing and deploying advanced statistical, machine learning, or enterprise data pipeline solutions.
• Strong proficiency in Python, including Pandas and related data engineering libraries.
• Strong SQL skills and experience integrating relational database systems.
• Hands-on experience designing and operating solutions in Azure cloud environments.
• Experience developing ETL workflows using Python and Microsoft technologies.
• Experience with schema enforcement, data validation, and quality assurance practices.
• Experience developing APIs and cloud-native data services.
• Familiarity with workflow orchestration tools such as Azure Data Factory.
• Experience with performance optimization, logging, and monitoring for enterprise-scale systems.
• Familiarity with open-source data processing and ML frameworks such as PyTorch, TensorFlow, NumPy, and scikit-learn.