Staff Data Platform Engineer

Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our dynamic teams work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world’s most premium platforms. Taking a Creative Science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Kargo is growing rapidly and currently has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland.

Who We Hire

Techies who want to build the future. Creatives who want to design it better. Communicators to win business. Collaborators to build it. Data pros who turn numbers into insights. Product builders who turn ideas into innovations. Anyone eager to be on a team that doesn’t stop to ask what’s next, because they’re already building it.

The Opportunity

Kargo is building toward a unified platform where advertisers run campaigns across CTV, web, mobile apps, and social entirely self-serve. This is the first time that capability goes directly into clients' hands. Clients will pull their own reports, debug their own setups, and ask why a campaign isn't pacing, so the data behind them must be quick to extend, stable enough to trust, and structured for automated triage. Our pipelines already run at that scale, but each demand is met one team at a time: reporting is bespoke, stability rests on each team's own practice and monitors, and triage depends on whoever knows the pipeline.

We're standing up a Data Platform team to solve these problems once for the whole company, and you'll be its founding engineer. Working directly with the Sr. Director of Data Engineering, you'll shape the standards and build the software that enables and enforces them, open the platform up to contributors across Kargo, and grow the team as its scope expands. You'll own it as a long-term product: modular tools and paved roads that let any team publish data and have it arrive discoverable, reliable, and observable enough to triage without tribal knowledge.

The Daily To-Do

• Build the data control plane. One place to see and govern what data products exist: schemas, lineage, ownership, freshness commitments, quality, access. Built for people browsing and agents querying.

• Build the paved road for standing up a data product. Libraries, SDKs, templates, and data-specific CI/CD on Kargo's engineering platform, plus a supported near-real-time pattern. Following the standard should be easier than bypassing it.

• Build the enforcement layer for the data standards. Schema registry, the contract validator and the CI step that runs it, automated certification.

• Make every data product observable by default. Freshness, volume, schema conformance, and quality instrumented by the paved road rather than hand-built per team, emitting into Kargo's existing monitoring with the ownership and lineage metadata that makes AI-assisted triage possible.