Data Collaboration Lead

Zeta Global

4d•$180,000 - $200,000•Remote

About The Position

Zeta Global is seeking a leader to own and evolve its data collaboration platform. This role is crucial for Zeta's strategy of working with large, security-conscious clients. The ideal candidate will be responsible for the platform's stability, scalability, security, and future development across various cloud ecosystems. This includes building upon the current cleanroom implementation and expanding capabilities to other cloud and data platforms like AWS and Databricks, while maintaining zero-copy, security, and enterprise trust. The role involves defining and executing a roadmap, establishing a scalable support and operating model, and staying technically involved in designing secure data collaboration workflows. Collaboration with product, sales, and client-facing teams is essential for go-to-market strategy, messaging, and supporting complex deals. Additionally, the role requires building internal expertise through enablement sessions and playbooks, and defining key success metrics to guide platform evolution.

Requirements

Leadership experience owning a data platform, product, or technical domain end to end.
Hands-on experience in Python, SQL, and Java or Ruby.
Hands-on experience with secure data sharing or collaboration patterns (e.g., cleanrooms, zero-copy architectures, policy-based access, governed computation).
Strong background in modern data platforms and cloud ecosystems (Snowflake, AWS, Databricks, or similar).
Ability to design and reason about secure, scalable architectures that meet enterprise and regulatory requirements.
Experience balancing technical depth with business ownership, including roadmap planning and GTM collaboration.
Comfort engaging directly with large enterprise clients on architecture, security, and value proposition.
A track record of building platforms that move from “working” to “scalable and repeatable.”

Nice To Haves

Think pragmatically. You default to the simplest solution that works and scales.
Prototype quickly. You’d rather ship a working automation this week than debate frameworks for a month.
Care about outcomes. An automation that isn’t used or doesn’t deliver value isn’t “done.”
Translate easily. You can talk ROI with stakeholders and implementation details with engineers.
Love the blank canvas. Ambiguity is fuel, not friction.

Responsibilities

Own the data collaboration platform: Act as the single-threaded owner for Zeta’s data collaboration product, responsible for stability, scalability, security posture, and long-term evolution across cloud architectures.
Evolve the architecture beyond its current foundation: Build on today’s cleanroom-based implementation and design equivalent capabilities across additional cloud and data platforms (e.g., AWS- and Databricks-based architectures) while preserving zero-copy, security, and enterprise trust guarantees.
Set and drive the roadmap: Define, prioritize, and execute a roadmap that balances client demand, technical feasibility, platform reuse, and long-term strategic value.
Build the support and operating model: Create the scalable support structure required to operate the platform at enterprise scale - documentation, patterns, tooling, escalation paths, and operational readiness.
Stay hands-on where it matters: Be technical enough to design and implement secure data collaboration workflows, including cleanroom-style patterns, access controls, and policy-driven computation.
Partner on go-to-market strategy: Work closely with product, sales, and client-facing teams to position data collaboration offerings, shape messaging, support complex deals, and ensure the platform is both sellable and deliverable.
Raise the internal bar: Build deep institutional knowledge around data collaboration: run enablement sessions, publish internal playbooks, and serve as the go-to expert across engineering, product, and GTM teams.
Measure what matters: Define success metrics - adoption, client outcomes, reliability, revenue impact - and use them to guide investment, iteration, and deprecation decisions.