Data Engineer (contract - to - hire, Part - time)

Data Engineer

Zeno Group is hiring a data engineer to join our team on a part-time, contract-to-hire basis (approximately 20 hours per week). This role reports into Zeno's AI & Innovation practice and works closely with our Data & Intelligence (D&I) team daily.

Zeno's D&I team performs both internal and client-facing data work and has built strong workflows to support it. We're investing in data engineering to take those workflows further: migrating to a new architecture, building reusable pipelines, and scaling what works across more clients.

You're joining active, revenue-generating client work with clear opportunities to improve how data moves through the organization.

This is also a role with influence. As the first dedicated data engineer at Zeno, you'll shape the tools, architecture, and practices that define how the organization works with data going forward.

We already have strong operational data workflows in place. This role focuses on scaling and modernizing that foundation into a more centralized, AI-ready architecture.

The team you're joining

AI & Innovation is a small team building a new practice inside a large organization. We move fast, cover a lot of ground, and hold ourselves to a high standard. A few things define how we work.

Craft over speed. We optimize for doing things well. AI and automation save us real time, and we reinvest those hours into work that's more durable and more useful. A pipeline that's clean, well-documented, and built to last is worth more than one that shipped yesterday and breaks next week.

Build what others can't access. We license tools when they solve the problem. But the work that differentiates Zeno is built in-house: proprietary data systems, AI products, and infrastructure that our clients and teams can't get anywhere else. You're rebuilding Zeno's data layer for where it needs to go next, not maintaining someone else's platform.

Makers who can hold a room. This role isn't heads-down-only. You'll be in architecture conversations, working through migration decisions with the DevOps team, and sitting across from analysts who need you to understand their client context before you build anything. We look for people who are strong technically and comfortable communicating what they know to people who don't share their vocabulary.

Radical visibility. We're a small team with outsized scope. There's no room to go quiet. We surface our work as we go, share what we're stuck on, flag when we have capacity, and keep each other in the loop without being asked. If you're the kind of person who finishes something and immediately shares it with the team, you'll thrive here. If you prefer to disappear into your work and surface only when it's done, this isn't the right fit.

About the Role:

• Transition data infrastructure to a modern architecture built around AWS.
• Improve and scale existing client data pipelines while keeping client deliverables running smoothly.
• Support the Snowflake migration by documenting current schemas, validating that the new architecture preserves existing functionality, and testing with real client data.
• Build the data layer for AI products, including ingestion pipelines, APIs, and programmatic access layers that connect data sources to LLM interfaces.
• Build and maintain data pipelines by configuring Fivetran connectors for paid media data, building pipelines for sources Fivetran doesn't cover, and writing validation and transformation steps.
• Connect data to BI tools by building views and clean tables that analysts can query directly without writing complex SQL.
• Support ongoing client work alongside client-facing analysts, from adjusting tables for new data cuts to standing up pipelines for new clients.

About You:

• 6+ years of hands-on data engineering experience. You've built pipelines, debugged data issues, and written clean SQL in a production environment.
• Comfortable with cloud data warehouses and modern tooling. Experience with at least one of Redshift, Snowflake, or BigQuery. You understand ETL/ELT patterns. Python for data work. AWS experience preferred.
• You hold your own in architecture conversations. You'd be in the room for decisions about schema design, warehouse selection, and data modeling, making sure what gets built serves the team's needs.
• You work well with analytically strong teammates. Our analysts have deep client and data experience from running operations at previous agencies. You need to understand their context and build things the team can maintain and use alongside you.
• Familiarity with and curiosity about LLM tooling, vector databases, or document processing pipelines matters here. Part of this role is identifying where LLMs plug into our data workflows.
• Consulting or agency experience is a plus.

Technical Environment

• Current: Snowflake, Fivetran, Tableau, Alteryx, Excel.
• Target: AWS (Redshift, S3, Lambda), Fivetran, Tray.ai, Tableau/PowerBI/Looker, and Hex.
• Adjacent: Claude/LLM integrations via MCP, custom dashboard development.
• Data types: paid media performance (Meta, Google, TikTok), earned media (Muckrack, Cision), employee engagement event data (Amplitude), creator/influencer campaign data.

Details:

• Part-time contract-to-hire, approximately 20 hours per week.
• Preferred location: Chicago.
• Reports to: Head of AI & Innovation