Senior Data Engineer

Everforth ECS is seeking a Senior Data Engineer to work remotely . 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. Key Responsibilities 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. Salary Range: $165,000-$180,000 General Description of Benefits 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.