Senior Data Engineer - Public Trust Clearance Required

Role Overview

Senior Data Engineer (Public Trust Clearance Required) working in the Microsoft Azure environment to design, develop, and maintain secure, scalable cloud data architectures and pipelines. You will support advanced analytics, fraud detection, machine learning, and investigative operations through reliable, high-quality data solutions.

Responsibilities

• Develop new datasets to support loan fraud identification, audits, and investigations.
• Optimize database query performance.
• Create and implement data models to improve efficiency and utility of databases.
• Propose and implement cloud architecture improvements to reduce cloud costs.
• Develop, optimize, and maintain ELT/ETL pipelines and monitor them to ensure performance and regular dataset updates.
• Work with a Cloud Architect to design new ways to access and transport data.
• Support development of dashboards/reports for data visualization and storytelling.
• Assist with ingestion, transformation, and configuration of data in Azure data lake / data warehouse.
• Explore, structure, and analyze unstructured and semi-structured data from SQL and lake environments.
• Author SOPs governing creation, maintenance, and monitoring of Azure data assets.
• Design and maintain ELT/ETL pipelines in Azure Synapse and Azure Machine Learning (SDK v1 and SDK v2), for efficient source data processing.

Requirements

• Bachelor’s degree in a relevant field (data engineering, computer science, data science, machine learning, mathematics) or 5 years of applied experience in related fields.
• Minimum 5 years experience with Azure DevOps, Azure Synapse, and Azure Machine Learning.
• 5+ years hands-on experience maintaining SQL databases and performing advanced work in SQL and T-SQL.
• 5+ years hands-on experience designing, implementing, and maintaining ELT/ETL processes in cloud-based data analytics environments.
• 3+ years hands-on experience working in Azure Synapse and Azure Machine Learning using a modern data stack.
• Certifications equivalent to DP-203 or DP-900.
• Proficiency in Python for data manipulation (Pandas required; PySpark/Polars preferred).
• Experience with reusable, modular code preferred.

Preferred Qualifications

• Code-first pipeline/infrastructure implementation (Python SDK, CLI, REST APIs, or IaC tooling).
• Use of source control and CI/CD workflows.
• 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 NLP.
• Experience supporting federal government or Inspector General organizations.
• Additional certifications preferred: AZ-305.