Senior 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 industrys 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 .

The Role

Werelooking for a Senior Data Engineer to design build andoperatethe data pipelines and aggregates that power Zetas AdTech platform. This is a hands-on individual contributor role focused on high-scale batch streaming data processing reliable data products and analytics-ready datasets that enable prediction agentic workflows BI reporting and measurement. You will partner closely with backend ML and product teams to deliver trusted well-modeled data withstrong performance quality and observability.

WhatYoullDo

• Build data pipelines: Develop robust batch and streaming pipelines (Kafka/Kinesis) to ingest transform and enrich large-scale event data (impressions clicks conversions costs identity signals).

• Create data aggregates & marts: Design andmaintaincurated aggregates and dimensional models for multiple consumersprediction models agents BI dashboards and measurement workflows.

• Data modeling & contracts: Define schemas data contracts and versioning strategies to keep downstream systems stable as sources evolve.

• Data quality & reliability: Implement validation anomaly detection backfills and reconciliation to ensure completeness correctness and timeliness (SLAs/SLOs).

• Performance & cost optimization:Optimizecompute/storage for scale (partitioning file sizing incremental processing indexing)balancinglatency throughput and cost.

• Orchestration & automation: Build repeatable workflows with scheduling/orchestration (e.g. AirflowDagster Step Functions) and CI/CD for data pipelines.

• Observability for data systems: Instrument pipelines with metrics logs lineage and alerting to accelerate detection and root-cause analysis of data issues.
• Security & governance: Apply least-privilege access PII-aware handling and governance controls aligned with enterprise standards.

Qualifications

• 5 years building production data pipelines and data products (batch and/or streaming) in a high-scale environment.
• Strong experience with SQL and data modeling (dimensional modeling star/snowflake schemas event modeling).

• Hands-on experience with streaming systems (Kafka preferred) and/or AWS Kinesis including event-driven designs.

• Proficiencyin one or more languages used for data engineering (Python Java Scala or Go).

• Experience with distributed data processing (Spark Flink or equivalent) and performance tuning at scale.

• Experience with AWS data services and cloud-native patterns (S3 Glue/EMR Athena Redshift etc. as applicable).

• Familiarity withlakehouse/table formats and large-scale storage patterns (e.g. Parquet; Iceberg/Hudi/Delta are a plus).

• Experience with orchestration/workflow tooling (Airflow/Dagster/Step Functions) and CI/CD for data workloads.

• Strong data quality/observability practices (tests monitoring lineage; understanding of SLAs/SLOs).

• Experience with SQL NoSQL data stores (e.g. Postgres/MySQL; DynamoDB/Cassandra/Redis) and choosing the right store per use case.
• Clear communicator and collaborator; able to work with mixed audiences and translate needs into reliable data interfaces.

Preferred Experience

• AdTech / programmatic advertising domain knowledge: DSP/SSP/exchange/RTB concepts and data flows.

• Experience building measurement pipelines (attribution incrementality lift or experimentation analytics).
• Experience supporting ML feature stores offline/online feature generation or model training datasets.

• Experience with real-time analytics stores (Druid/ClickHouse/Pinot) and high-cardinality aggregation strategies.

• Deep knowledge of data governance/privacy including PII handling and consent-aware data processing.

• Open-source contributions publications or conference speaking.

• BS/MS in CS/Engineering or equivalent practical experience.

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 $165000 - $175000depending 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 individuals 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.

Were 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: IN THE NEWS!

Experience:

Senior IC