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Salary: USD 165,000 - 185,000 / annual
Zeta Global (NYSE: ZETA) is an AI-powered marketing cloud that helps enterprise customers acquire, grow, and retain customers more efficiently. The company unifies identity, intelligence, and omnichannel activation through the Zeta Marketing Platform (ZMP), powered by one of the industry's largest proprietary databases and AI.
As a Senior Data Platform Engineer, you will build and operate the data infrastructure supporting Zeta's products, analytics, machine learning, and AI systems. This is a broad platform role where engineers take ownership across Lakehouse architecture, distributed compute, data quality, governance, lineage, security, access controls, and operational systems. Your focus areas will evolve with team priorities, and you will contribute across the platform as needed.
The team develops tooling for type-safe, testable data pipelines and operates Spark workloads on dynamically sized Hadoop clusters backed by EC2 Spot instances. You will work closely with data engineers, data scientists, infrastructure teams, and product teams to make data dependable, easy to find, secure to use, and cost-effective to process.
Key responsibilities include: building and operating Lakehouse, Spark, and distributed data-processing systems; improving performance, reliability, cost, and operational visibility of platform workloads; developing capabilities for data quality, governance, lineage, metadata, discoverability, security, and access control; building data context for trusted reporting, ML models, and AI agents; evaluating compute and query engines for read-heavy workloads; assessing real-time OLAP technologies; improving deployment, observability, incident response, developer tooling, and platform operations; partnering with data scientists and engineers to improve their platform experience; contributing to open-source projects including Spark, Iceberg, and Airflow; and mentoring engineers through code reviews, pairing, design discussions, and knowledge-sharing.
This is a hybrid role based in either San Mateo, CA or San Francisco, CA.
QUALIFICATIONS:
- 7+ years of software engineering experience
- Strong experience in Python, Scala, Java, or another JVM language
- Experience with Spark or another distributed data-processing framework
- Experience building or operating production data platforms, backend systems, or distributed systems
- Familiarity with at least one of: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP
- Working knowledge of AWS services such as EC2, S3, Athena, and IAM
- Experience improving production reliability through monitoring, alerting, deployment automation, and incident response
- Strong analytical, communication, and collaboration skills
- Plus: Experience with Kubernetes, Terraform, Airflow, Trino, ClickHouse, Starrocks, or Pinot
