Zeta Global

Zeta Global

Zeta Global provides an AI-powered marketing cloud that enables enterprises to acquire, grow, and retain customers through precision marketing, leveraging data science, advanced analytics, and machine learning to create optimized customer experiences.

Media
1K-5K
Founded 2007

Description

  • Design, build, and operate batch and streaming data pipelines for large-scale event data ingestion, transformation, and enrichment.
  • Create and maintain curated data aggregates and dimensional models for prediction, agents, BI dashboards, and measurement workflows.
  • Define schemas, data contracts, and versioning strategies to keep downstream systems stable as source data evolves.
  • Implement data validation, anomaly detection, backfills, and reconciliation to ensure data completeness, correctness, and timeliness.
  • Optimize compute and storage for scale by improving partitioning, file sizing, incremental processing, and indexing.
  • Build repeatable orchestration and automation workflows for data pipelines using scheduling tools and CI/CD.
  • Instrument data systems with metrics, logs, lineage, and alerting to improve observability and root-cause analysis.
  • Apply least-privilege access, PII-aware handling, and governance controls aligned with enterprise standards.
  • Partner closely with backend, ML, and product teams to deliver trusted, well-modeled data products.

Requirements

  • 5+ years of experience building production data pipelines and data products in a high-scale environment.
  • Strong SQL skills and experience with data modeling, including dimensional modeling, star/snowflake schemas, and event modeling.
  • Hands-on experience with streaming systems such as Kafka preferred or AWS Kinesis, including event-driven designs.
  • Proficiency in one or more data engineering languages such as Python, Java, Scala, or Go.
  • Experience with distributed data processing frameworks such as Spark, Flink, or equivalent, including performance tuning at scale.
  • Experience with AWS data services and cloud-native patterns such as S3, Glue/EMR, Athena, and Redshift.
  • Familiarity with lakehouse or table formats and large-scale storage patterns, including Parquet; Iceberg, Hudi, or Delta are a plus.
  • Experience with orchestration and workflow tooling such as Airflow, Dagster, or Step Functions, plus CI/CD for data workloads.
  • Strong data quality and observability practices, including tests, monitoring, lineage, and understanding of SLAs/SLOs.
  • Experience with SQL and NoSQL data stores such as Postgres, MySQL, DynamoDB, Cassandra, or Redis.
  • Clear communication and collaboration skills, with the ability to translate needs into reliable data interfaces.
  • Preferred: AdTech or programmatic advertising domain knowledge, including DSP, SSP, exchange, and RTB concepts and data flows.
  • Preferred: Experience building measurement pipelines for attribution, incrementality, lift, or experimentation analytics.
  • Preferred: Experience supporting ML feature stores, offline/online feature generation, or model training datasets.
  • Preferred: Experience with real-time analytics stores such as Druid, ClickHouse, or Pinot and high-cardinality aggregation strategies.
  • Preferred: Deep knowledge of data governance and privacy, including PII handling and consent-aware data processing.
  • Preferred: Open-source contributions, publications, or conference speaking.
  • Preferred: BS/MS in Computer Science, Engineering, or equivalent practical experience.

Benefits

  • Unlimited PTO.
  • Excellent medical, dental, and vision coverage.
  • Employee equity.
  • Employee discounts.
  • Virtual wellness classes.
  • Pet insurance.
  • Salary range of $165,000 to $175,000 depending on location and experience.

Interested in this position?

Apply directly on the company website

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