Staff Data Engineer

WHO WE ARE 

Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire grow and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP) our vision is to make sophisticated marketing simple by unifying identity intelligence and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more go to www.zetaglobal.com.

The Opportunity 

We are looking for a Staff Data Engineer to lead the design and implementation of a unified semantic data layer that spans all of Zeta’s data sources—both data at rest and data in motion. This role sits at the intersection of data engineering platform architecture and AI enablement. You will be responsible for building a middleware semantic layer (using Cube Core or similar technologies) that exposes clean governed multi-tenant data via standardized APIs and tool interfaces enabling AI agents and LLMs to query reason over and act on Zeta’s data with high performance security and compliance. 

This is a high-impact high-visibility role that will shape how Zeta’s AI systems consume and interact with data across the organization. 

What You’ll Do 

Semantic Layer Architecture & Development 

• Design and build a centralized semantic data layer using Cube Core (or equivalent technology such as Headless BI dbt Metrics Layer or Metriql) that provides a unified governed abstraction over all company data sources. 

• Define semantic models metrics dimensions and relationships that map to business domains across marketing advertising identity resolution and customer analytics. 

• Expose the semantic layer via REST/GraphQL APIs and MCP-compatible tool interfaces purpose-built for consumption by AI agents and LLMs. 

Data Source Integration & Unification 

• Integrate and unify data from heterogeneous systems including MySQL DynamoDB Aerospike Snowflake Amazon S3 (data lakes) Apache Kafka Amazon SQS and other internal data stores. 

• Build connectors adapters and federation layers to query across both operational (OLTP) and analytical (OLAP) data sources in a performant cost-efficient manner. 

• Ensure seamless handling of both data at rest (warehouses lakes databases) and data in motion (streaming platforms event buses message queues). 

AI & LLM Enablement 

• Design tool interfaces and API contracts that allow AI agents to discover available data understand schema semantics and generate accurate queries autonomously. 

• Collaborate with AI/ML teams to optimize the semantic layer for LLM-generated SQL natural language querying retrieval-augmented generation (RAG) and agentic workflows. 

• Implement guardrails query validation and cost controls to prevent runaway queries from AI-generated workloads. 

Multi-Tenancy Security & Compliance 

• Architect the semantic layer with native multi-tenant isolation ensuring strict data segregation and tenant-scoped access controls. 

• Implement row-level security column-level masking and attribute-based access controls (ABAC) to enforce data governance policies. 

• Ensure compliance with SOC 2 GDPR CCPA and industry-specific regulations governing data access PII handling and cross-border data flows. 

Performance Scalability & Reliability 

• Design for horizontal scalability to support thousands of concurrent queries from AI agents internal dashboards and customer-facing products. 

• Implement intelligent caching (pre-aggregation materialized views query result caching) to deliver sub-second response times for common query patterns. 

• Build observability into the semantic layer with comprehensive metrics logging alerting and query performance profiling. 

Technical Leadership & Collaboration 

• Serve as the technical authority on data architecture decisions authoring ADRs (Architecture Decision Records) and reference architectures. 

• Mentor and guide senior engineers on best practices for semantic modeling data governance and API design. 

• Partner cross-functionally with Product Data Science Platform Engineering InfoSec and Compliance teams to align the data layer with business objectives. 

What We’re Looking For 

Required Qualifications 

• 10+ years of experience in data engineering data architecture or platform engineering with at least 3 years operating at a Staff/Principal level. 

• Deep hands-on expertise with multiple data stores: relational (MySQL/PostgreSQL) NoSQL (DynamoDB Aerospike MongoDB) cloud data warehouses (Snowflake BigQuery Redshift) and data lakes (S3 Delta Lake Iceberg). 

• Strong experience with streaming and messaging systems: Apache Kafka Amazon SQS/SNS Kinesis or equivalent. 

• Proven experience building or operating semantic/metrics layers using Cube.js/Cube Core dbt Metrics LookML or similar technologies. 

• Expert-level SQL skills and experience with query optimization across distributed systems. 

• Production experience designing multi-tenant data platforms with strict security and isolation requirements. 

• Strong understanding of data governance access control models (RBAC ABAC) and compliance frameworks (SOC 2 GDPR CCPA). 

• Experience designing and exposing APIs (REST GraphQL) for data consumption at scale. 

• BS/MS in Computer Science Data Engineering or equivalent practical experience. 

Preferred Qualifications 

• Experience building data interfaces specifically for AI/ML consumption including tool-use APIs for LLM agents MCP (Model Context Protocol) or function-calling patterns. 

• Familiarity with AI orchestration frameworks (LangChain LlamaIndex Semantic Kernel) and how they interact with external data tools. 

• Experience with infrastructure-as-code (Terraform Pulumi) container orchestration (Kubernetes ECS) and CI/CD pipelines for data platform deployments. 

• Background in MarTech/AdTech data domains: identity graphs audience segmentation campaign analytics attribution modeling or real-time bidding data. 

• Contributions to open-source data tools or published thought leadership on semantic layers data mesh or AI-enabled data architectures. 

BENEFITS & PERKS

• Unlimited PTO
• Excellent medical dental and vision coverage
• Employee Equity
• Employee Discounts Virtual Wellness Classes and Pet Insurance And more!!

SALARY RANGE

The salary range for this role is $170000 - $200000 depending on location and experience. 

PEOPLE & CULTURE AT ZETA

Zeta considers applicants for employment without regard to and does not discriminate on the basis of an individual’s sex race color religion age disability status as a veteran or national or ethnic origin; nor does Zeta discriminate on the basis of sexual orientation gender identity or expression.  

We’re committed to building a workplace culture of trust and belonging so everyone feels invited to bring their whole selves to work. We provide a forum for employees to celebrate support and advocate for one another. Learn more about our commitment to diversity equity and inclusion here:  https://zetaglobal.com/blog/a-look-into-zetas-ergs/ 

ZETA IN THE NEWS!

https://zetaglobal.com/press/?cat=press-releases 

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What We Do

Zeta Global (NYSE: ZETA) is the AI Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire grow and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP) our vision is to make sophisticated marketing simple by unifying identity intelligence and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world.

Why Work With Us

At Zeta people have the freedom to think creatively take initiative and grow. We value curiosity innovation and teamwork empowering everyone to use AI and technology in smarter ways to drive impact for clients consumers and each other while shaping the future together.

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