Staff Data Engineer

Zeta Global

Staff Data Engineer at Zeta Global leading the design and implementation of a unified semantic data layer. Focused on integrating diverse data sources for enhanced AI and analytics capabilities.

Posted 4/17/2026full-timeRemote • 🇺🇸 United StatesLead💰 $170,000 - $200,000 per yearWebsite

Tech Stack

Tools & technologies

Amazon RedshiftApacheBigQueryCloudDistributed SystemsDynamoDBGraphQLJavaScriptKafkaMongoDBMySQLNoSQLPostgresSQL

About the role

Key responsibilities & impact

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.
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).

Requirements

What you’ll need

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.

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata architectureplatform engineeringSQLquery optimizationsemantic modelsmetrics layersdata governancedata integrationdata modeling

Soft Skills

leadershipcommunicationproblem-solvingcollaborationorganizational skills

Certifications

BS in Computer ScienceMS in Computer ScienceData Engineering certification