Senior Data Engineer (Azure Data Platform & Cloud Analytics)

WINTrio LLC is seeking an experienced Senior Data Engineer to support Federal agencies in designing, developing, and maintaining modern cloud-based data platforms that enable advanced analytics, machine learning, fraud detection, and mission-critical decision making. The successful candidate will architect scalable Azure data solutions, develop high-performance ELT/ETL pipelines, optimize enterprise databases, and collaborate with Data Scientists to support AI and machine learning initiatives.

Responsibilities:

• Design, implement, and maintain scalable cloud-based data architectures supporting enterprise analytics and machine learning
• Develop, optimize, and maintain ELT and ETL pipelines for structured, semi-structured, and unstructured datasets
• Design and support Azure Synapse Analytics, Azure Machine Learning, and Azure Data Lake Storage (ADLS) environments
• Develop reusable, modular Python code for data engineering, automation, and data processing
• Build, optimize, and maintain SQL Server and PostgreSQL databases, including advanced SQL and T-SQL operations
• Optimize data ingestion, processing, transformation, and storage using modern data engineering best practices
• Design and maintain data models, data dictionaries, ER diagrams, metadata, and technical documentation
• Implement source control, CI/CD pipelines, version control, logging, monitoring, validation, and error handling across all data assets
• Develop and maintain infrastructure using code-first approaches including Python SDK, CLI, REST APIs, and Infrastructure as Code (IaC)
• Collaborate with Data Scientists to develop scalable machine learning data pipelines and analytics environments
• Develop Standard Operating Procedures (SOPs) governing the development, deployment, validation, monitoring, and maintenance of enterprise data pipelines
• Evaluate and implement emerging AI technologies, AI coding assistants, and LLM-enabled data engineering capabilities to improve engineering productivity and automation

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related discipline
• Minimum five (5) years of hands-on experience maintaining SQL databases and performing advanced SQL and T-SQL development
• Minimum five (5) years of experience designing, implementing, and maintaining ELT/ETL pipelines in cloud-based data analytics environments
• Minimum three (3) years of experience with Azure Synapse Analytics and Azure Machine Learning using modern Azure data services
• Minimum three (3) years of professional Python development experience with Pandas. Experience with PySpark and Polars is preferred
• Experience developing reusable, modular, maintainable Python code
• Experience designing cloud-native data architectures using Azure Data Lake Storage (ADLS), Azure Synapse, and Azure Machine Learning
• Experience implementing source control, Git workflows, and CI/CD pipelines
• Experience developing infrastructure using Python SDK, CLI, REST APIs, and Infrastructure as Code (IaC) tools
• Strong analytical, documentation, communication, and problem-solving skills
• Experience supporting Federal Government agencies
• Experience designing enterprise Azure data platforms and analytics environments
• Experience supporting AI, machine learning, and cloud-native analytics solutions
• Experience implementing source-controlled, code-first data engineering practices
• Familiarity with AI coding assistants and Large Language Model (LLM) integration patterns
• Experience working within Agile development environments