What you will be doing:

• Perform all duties and maintain all standards in accordance with company policies, procedures, and internal controls such as SOX.
• Design, implement, and maintain cloud-based data pipelines to enable efficient storage, processing, and analysis of large volumes of data.
• Collaborate with data engineers, and other stakeholders to understand requirements and translate them into scalable and reliable data platform architectures.
• Evaluate and select appropriate cloud infrastructure and services to support data storage, processing, and analytics needs, considering factors such as scalability, performance, extendibility, cost, and security.
• Implement data ingestion pipelines, integrating various, disparate data sources and ensuring data quality, integrity, and timeliness.
• Design and optimize data storage solutions, including data lakes, data warehouses, and data marts, to support different types of data processing and analysis.
• Implement data processing and transformation workflows using technologies such as Azure Spark, Azure SQL Pools / data warehouses or other cloud-native data processing services.

What you will likely bring:

• 3+ years’ experience in data engineering, analytics engineering, DataOps, business intelligence engineering, or a related technical field.
• Strong SQL skills and experience working with data pipelines, data platforms, data warehouses, data lakes, or similar data environments.
• Experience gathering requirements from business stakeholders and explaining technical concepts clearly to technical and nontechnical audiences.
• Strong analytical, strategic-thinking, and creative problem-solving skills, with curiosity to identify trends, investigate details, and improve processes.
• Excellent written and verbal communication skills, with the ability to synthesize significant amounts of information and tailor it to the intended audience.

What could set you apart:

• Cloud & DevOps: Hands-on Azure development beyond data pipelines, including infrastructure-as-code (e.g., Bicep, Terraform, or ARM) and DevOps practices such as CI/CD, Git-based source control workflows, and automated deployment of data assets.
• AI-assisted development: Practical experience using AI coding assistants (e.g., ChatGPT, GitHub Copilot/Codex) to accelerate development, testing, and code review within a disciplined, version-controlled workflow.
• Applied AI / GenAI: Exposure to building AI-driven solutions — retrieval-augmented generation (RAG), agentic workflows, vector databases, and orchestration frameworks such as LangChain or LangGraph.
• Lightweight application development: Ability to stand up simple internal applications or APIs (e.g., Python, FastAPI) to surface data and tooling to end users.

Whatever your career journey, we’ll help you find the right path. Through our training courses, mentorship, and continuous support, you’ll get everything you need to thrive. At Epicor, your success is our success. And that success really matters, because we’re the essential partners for the world’s most essential businesses—the hardworking companies who make, move, and sell the things the world needs.

Recruiter: