Data Engineer

Responsibilities

• 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
• Required Skills
• 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

Requirements

• 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
• To learn mo

Benefits

Additional Information

No other company in our industry is supercharging the way they work and serve their clients like OneDigital. Fresh thinking has always been the core of OneDigital's vision and growth strategy. It's how we stand out in our industry, it's how we stay competitive and resilient in a changing world. Most importantly, our innovative approach is helping more people do their best work and live their best lives. Innovation fuels our employee experience by making it easier to do your best work anytime, anywhere and from any device. And our tech-based products for clients are a game changer in our industry. If you thrive on change and innovation, OneDigital is the career choice for you. Our Newest Opportunity: We're building a modern, AI-native data engineering function on Azure + Snowflake, where AI coding agents are first-class contributors to the dev workflow. You'll join a small team owning the full data lifecycle - ingestion, modeling, governance - and ship production pipelines from day one. This is a great seat for someone early in their career who wants to grow fast in an environment where AI tooling is the default, not an afterthought. We're optimizing for learning velocity over years of experience . If you have 0-2+ years and a strong foundation, you're in scope.

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