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. This role requires strong expertise in Azure data services, SQL, Python, cloud-native engineering, and modern data architecture., * 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.

Work Authorization: U.S. Citizenship required. Candidates must be eligible to obtain and maintain a Public Trust clearance., * 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.

Technical Areas

Data Engineering

• Data Engineering

• ELT

• ETL

• Data Pipelines

• Data Architecture

• Data Integration

• Data Transformation

Azure Data Platform

• Azure Synapse Analytics

• Azure Machine Learning

• Azure Data Lake Storage (ADLS)

• Modern Data Stack

• Cloud Data Architecture

Database Engineering

• SQL Server

• PostgreSQL

• SQL

• T-SQL

• Data Modeling

• Query Optimization

• Performance Tuning

• Data Dictionaries

• ER Diagrams

Automation & Cloud Engineering

• Python SDK

• CLI

• REST APIs

• Infrastructure as Code (IaC)

• Source Control

• CI/CD

• Version Control

• Logging & Monitoring

Tools & Platforms

Platforms

• Microsoft Azure

• Azure Synapse Analytics

• Azure Machine Learning

• Azure Data Lake Storage (ADLS)

Programming Languages

• Python

• SQL

• T-SQL

Frameworks & Libraries

• Pandas

• PySpark

• Polars

Databases

• SQL Server

• PostgreSQL

Cloud Platforms

• Microsoft Azure

DevSecOps & Automation

• Git

• Azure DevOps

• GitHub

• GitHub Actions

• GitLab CI/CD

• CI/CD Pipelines

• Infrastructure as Code (IaC)

Monitoring & Reporting

• Azure Monitor

• Power BI

• Grafana

• Microsoft Excel

Preferred Certifications

• Microsoft Certified: Azure Data Engineer Associate (DP-203), * 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.

• Full-time position.

• Remote within the United States.

• Standard business hours Monday through Friday.

• Occasional travel may be required to support customer meetings, workshops, and program activities.

WINTrio Benefits

• Healthcare (Medical, Dental, and Vision)

• Flexible Spending Account (FSA) and Health Savings Account (HSA)

• 401(k) and Retirement Savings Plan

• Annual Bonus and Profit Sharing Opportunities

• Paid Time Off (PTO) and Vacation

• Employee Assistance Program (EAP)

• Life, Personal, and Voluntary Disability Insurance

Growth Opportunities

This position provides opportunities to work on enterprise-scale Azure data platforms, Artificial Intelligence, Machine Learning, cloud modernization, advanced analytics, automation, and mission-critical Federal technology programs. WINTrio is an employee-driven company where innovation, technical excellence, and continuous learning drive our success.