The Senior Data Engineer designs, develops, and maintains secure, scalable cloud-based data architectures and data pipelines. The position supports advanced analytics, fraud detection, machine learning, and investigative operations by delivering reliable, high-quality data solutions within the Microsoft Azure environment. Key Responsibilities: • Develop new datasets to support loan fraud identification, audits, and investigations. • Optimizes the performance of common queries in the database. • Creates and implements data models to improve the efficiency and utility of the database. • Proposes and implements architectural improvements to reduce cloud costs. • Develops, optimizes, and maintains ELT/ETL pipelines • Monitors pipelines to ensure performance and regular updating of datasets. • Works with a Cloud Architect to develop new ways of accessing and transporting data. • Aids in the development of dashboards or reports to visualize data and storytelling. • Assists in ingestion, transformation, and configuration of data in cloud-based data lake or data warehouse. • Assists with exploration, structuring, and analysis of unstructured and semi-structured data from SQL and data lake environments. • In collaboration with data architecture staff, authors SOPs governing creation, maintenance, and monitoring of all assets in Azure environment. • Design, implement, and maintain ELT/ETL pipelines for efficient processing of source data in Azure Synapse and Azure Machine Learning (using SDK V1 and SDK V2). Required: • Bachelor's degree in data engineering, computer science, data science, machine learning, mathematics, or a related field; OR 5 years of applied work experience in any of the same fields. • Minimum 5 years of experience in Azure DevOps, Azure Synapse and Azure Machine Learning. • Five (5) years of hands-on experience in each of the following: a. Maintaining SQL databases and conducting advanced operations in SQL and T-SQL. b. Designing, implementing, and maintaining ELT/ETL processes in cloud-based data analytics environments. • Three (3) years of hands-on experience in each of the following: A. Working in Azure Synapse and Azure Machine Learning, with the modern data stack. Certifications equivalent to DP-203 or DP-900. B. Manipulating data in Python. Pandas required. PySpark/Polars preferred. Experience developing reusable, modular code preferred. Preferred: • Implementing pipelines and infrastructure using code-first approaches (Python SDK, CLI, REST APIs, or IaC tooling) • Additional certifications preferred: AZ-305 • Implementing source control and CI/CD workflows • Demonstrated familiarity with AI coding assistants and LLM integration patterns • Experience with REST APIs, Infrastructure as Code (IaC), and Azure DevOps. • Experience supporting AI, Large Language Models (LLMs), and Natural Language Processing (NLP). • Experience supporting Federal Government or Inspector General organizations.