Data Engineer

We are seeking a highly skilled, future-ready Data Engineer to help build the data platform that powers trusted Business Intelligence today and AI-enabled experiences tomorrow. This role is grounded in strong data engineering fundamentals - scalable pipelines, clean data modeling, reliable integrations, database performance, governance, and data quality - while also advancing the organization's ability to support front-end data products, MCPs, and AI-agent workflows.

The ideal candidate brings deep Python capability, disciplined Git Hub-based development, deployment awareness, excellent technical documentation habits, and strong ownership of production-quality data solutions. SS&E is a tech-forward organization that believes in the responsible use of AI, with responsibility and accountability remaining with the individual. This position encourages the responsible use of AI-assisted engineering tools such as OpenAI Codex, Claude Code, or comparable tools under SS&E's enterprise agreements to support development, testing, refactoring, debugging, documentation, and codebase understanding;

however, these tools should not be relied upon as a substitute for sound data engineering judgment, clean architecture, secure coding practices, or hands‑on technical ownership.

• Bachelor's or Master's Degree in Computer Science, Engineering, Data Analytics, Information Systems, or related field.
• 1‑2 years of experience as a Data Engineer, Analytics Engineer, Software Engineer with a data focus, or similar technical role building data pipelines, models, and data platforms.
• Strong foundation in data engineering fundamentals, including ETL/ELT pipelines, data modeling, relational databases, API integrations, data validation, orchestration concepts, and scalable data architecture.
• Expertise in Python, including experience building production‑ready scripts, data pipelines, automation workflows, APIs, backend services, or data processing frameworks.
• Proficiency in SQL, including SQL-based data modeling, query optimization, transformation logic, and troubleshooting.
• Hands‑on experience with SQL Server, Azure SQL Managed Instance, Snowflake, or other relational database systems.
• Experience extracting, transforming, and integrating data from complex APIs, SaaS platforms, operational systems, and external data sources.
• Experience using Git Hub for version control, pull requests, code review, branching strategies, release documentation, and collaborative development workflows.
• Experience creating and maintaining clear technical documentation for data pipelines, data models, APIs, deployment steps, system dependencies, support procedures, and runbooks.
• Knowledge of how data infrastructure supports BI tools, React‑based front ends, internal applications, and AI‑enabled workflows.
• Familiarity with Azure or AWS cloud services used for data storage, compute, integration, deployment, and monitoring, with preference for Azure‑based data environments.
• Experience developing governed datasets, curated reporting layers, or datasets for Business Intelligence, visualization, and operational analytics use cases.
• Strong analytical, troubleshooting, and problem‑solving skills with the ability to improve existing systems without disrupting business operations.
• Effective communication skills and ability to collaborate with technical and non‑technical stakeholders.

• Experience designing AI‑ready data infrastructure, MCPs, governed context layers, or data services that support internal AI agents and automation.
• Experience using OpenAI Codex, Claude Code, or comparable AI‑assisted engineering tools in Git Hub‑connected, CLI, IDE, or deployment‑adjacent workflows under appropriate enterprise usage standards.
• Experience with No
  
  SQL databases.
• Experience writing developer‑friendly documentation, data dictionaries, architecture notes, and operational support guides.

• Design, build, and optimize scalable data pipelines using strong data engineering fundamentals, including ETL/ELT design, data modeling, validation, monitoring, and performance‑aware architecture.
• Develop production‑ready Python scripts,…