Data Engineer, Data Cloud International at Zeta Global | AdTechTalent
Data ScienceYesterdayOn-site
Zeta Global
Data Engineer, Data Cloud International
data engineeringSQLPythonAWSS3AthenaGlueETLELTAirflowPrefectSnowflakeDatabricksRedshiftHivePrestoGitJSONParquetORCAPIsdata validationtechnical documentationAI-assisted tools
Key details
Salary
Not specified
Employment type
Full-time
Seniority
Mid-level
Years experience
3-5
Location
Copenhagen, Denmark
Full job description
Zeta Global seeks a Data Engineer based in Copenhagen, Denmark to operationalize Zeta’s Data Cloud internationally. The role involves practical data engineering to convert data partnerships into revenue-generating assets supporting product innovation and growth. Responsibilities include building and automating data workflows, evaluating datasets, scripting data transformations, querying with SQL and Athena, validating data, producing technical documentation, and collaborating with internal and external technical teams. Required skills include 3-5 years experience in data engineering or related fields, proficiency in SQL, Python, AWS services (S3, Athena, Glue), ETL/ELT concepts, working with structured and semi-structured data formats, API data sources, and use of orchestration tools like Airflow or Prefect. Strong English communication and ability to work independently are essential.
What you'll do
Build and automate data workflows for new and existing data partnerships
Create repeatable ingestion, transformation, and replication processes for partner data feeds
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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 field mappings, data dictionaries, process notes, data flow summaries, and partner integration documentation
Use AI-assisted tools to accelerate data investigation, documentation, code generation, workflow prototyping, and repeatable analysis
Communicate with technical contacts at data partners via email and occasional technical calls
Translate partner data delivery requirements into practical ingestion and automation workflows
Work with internal teams across Operations, Product, Engineering, Compliance, and Data Cloud
Contribute to reusable templates, naming conventions, and documentation standards for partner data onboarding
Requirements
Strong written and spoken English
3–5 years of relevant experience in data engineering, analytics engineering, technical data operations, cloud data automation, or similar
Practical experience writing SQL to query, validate, and transform data
Hands-on experience with Python for scripting, automation, or data manipulation
Familiarity with AWS data services, especially S3 and Athena; experience with Glue strongly preferred
Understanding of ETL/ELT concepts and data movement between systems
Experience with structured and semi-structured data formats including large delimited files, JSON, Parquet, ORC
Comfortable reading technical documentation and working with API-based data sources
Ability to work with large datasets and investigate schema, count, format, or transformation issues
Comfortable collaborating with internal technical teams and external partner technical contacts
Ability to work independently on defined tasks while escalating blockers or risks appropriately
