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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Digital Insurance LLC - **Location:** Atlanta, GA, United States - **Experience:** Starter - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, ARM Architecture, Microsoft Azure, Code Review, Continuous Integration, Data Governance, Data Hub, Cursor (Graphical User Interface Elements), DevOps, Github, Python (Programming Language), Microsoft Dynamics, Microsoft SQL Server, Object-Oriented Software Development, Query Optimization, SQL Databases, YAML, Data Ingestion, Azure Data Factory, GitHub Copilot, Power Platform Integration, Large Language Models, Snowflake, Pandas, Git Flow, Software Version Control, Data Pipelines, Key Vault - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=e26052677f506521 ## About the Role Do you have experience in YAML?, We're optimizing for learning velocity over years of experience. If you have 0-2+ years and a strong foundation, you're in scope., * Python - comfortable writing clean, modular code; familiar with pandas, requests, basic OOP, virtualenvs/uv * SQL - strong fundamentals (joins, window functions, CTEs, query optimization) * Azure Data Factory - hands-on pipeline development, parameterization, triggers, linked services * Azure services - working knowledge of Storage (Blob/ADLS), Key Vault, DevOps (pipelines, repos) * Snowflake - has built or contributed to real warehouses; understands warehouses, roles, micro-partitions * Source control - Git workflows, PRs, branching AI / Agentic Skills (Required at conceptual level) You don't need to have shipped LLM apps in production, but you should be conversant in: * AI coding agents - used Copilot, Cursor, Claude Code, or equivalent for real work (not just demos) * LLMs - understand prompting, context windows, tool use / function calling, structured outputs * RAG - know what it is, when to use it, the basic architecture (embeddings, vector store, retrieval, generation) * MCP (Model Context Protocol) - bonus if you've used it, but willingness to learn quickly is required; we use Atlan MCP and Snowflake MCP Nice to Have * Coalesce, dbt, or another transformation framework * Experience with Dataverse / Dynamics 365 / Power Platform data sources * Atlan or another data catalog/governance tool * CI/CD experience with Azure DevOps YAML pipelines * Exposure to vector databases (Pinecone, Weaviate, pgvector, Snowflake Cortex) * Personal projects with LLMs, agents, or AI tooling - show us your GitHub Mindset We're Hiring For * Learning mindset. Tooling will change every 6 months. We need someone who's energized by that, not exhausted by it. * Bias to ship. Pragmatic over perfect. Get it working, get it reviewed, iterate. * AI-leveraged. You treat AI agents as force multipliers. You know when to delegate to them and when to think yourself. * Ownership. When a pipeline breaks at 2am, you don't wait to be told. * Clear written communicator. Async-friendly, document-as-you-go. Education * Bachelor's degree in CS, Engineering, Math, Stats, or related field - or equivalent practical experience. Bootcamp grads and self-taught engineers with solid portfolios welcome. Logistics * Location: Atlanta, GA - hybrid * Experience: 2+ years preferred; fresh graduates with strong projects encouraged to apply ## Description * Build and maintain ingestion pipelines into Snowflake from a range of source systems (Dataverse, SQL Server, APIs, files) using Azure Data Factory Develop transformation logic in Snowflake following a medallion architecture (bronze silver * gold), using Coalesce for orchestrated SQL transformations * Write Python for orchestration, automation, custom connectors, and lightweight services * Partner with AI coding agents (GitHub Copilot, Claude Code, Cortex) as part of your daily workflow - you're expected to be effective at directing them, not just using autocomplete * Apply data governance and lineage standards through Atlan * Participate in code reviews, CI/CD via Azure DevOps, and on-call rotations for production pipelines * Contribute to internal documentation and runbooks ## Related Videos - [CI/CD with Github Actions](https://www.wearedevelopers.com/videos/856-ci-cd-with-github-actions) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)