Global Data Cloud Engineer — Partnerships & Automation

Zeta Global; København; On-site; DKK 600,000 - 900,000; Full time

Job summary

Zeta Global is seeking a Data Engineer to help accelerate the operationalization of Zeta’s Data Cloud across international markets. The role focuses on practical data engineering: ingestion, transformation, validation, and documentation of partner data feeds using AWS services like S3, Athena, and Glue.

You will work hands-on across cross-functional teams with a focus on scalable data workflows, API-based data exchange, and AI-assisted tooling to automate and document processes.

Qualifications

• Strong English communication across international teams.
• 3–5 years of data engineering or related experience.
• Hands-on SQL, Python, and AWS data services experience.

Responsibilities

• Build and automate data workflows for new and existing data partnerships.
• Create repeatable ingestion, transformation, and replication processes for partner data feeds.
• Evaluate incoming datasets for structure, usability, coverage, completeness, and quality.
• Write scripts to transform, normalize, move, and prepare data for analysis or downstream use.
• Use SQL and Athena to query large datasets, validate outputs, and generate reporting tables or extracts.
• Build lightweight validation checks for files, schemas, counts, formats, and expected values.
• Produce clear technical documentation including data dictionaries and mappings.
• Collaborate with internal teams and external partners to translate requirements into ingestion/workflow solutions.
• Contribute to reusable templates and documentation standards for partner data onboarding.

Skills

SQL

Python

AWS S3

AWS Athena

AWS Glue

ETL/ELT workflows

Data ingestion

APIs

Airflow

Git

Data validation

Data dictionaries

Tools

Airflow

Prefect

Snowflake

Databricks

Redshift

Hive

Presto

Git

Job description

Zeta Global is seeking a Data Engineer to help accelerate the operationalization of Zeta’s Data Cloud across international markets. The role focuses on practical data engineering: ingestion, transformation, validation, and documentation of partner data feeds using AWS services like S3, Athena, and Glue.

You will work hands-on across cross-functional teams with a focus on scalable data workflows, API-based data exchange, and AI-assisted tooling to automate and document processes.