AS
Avanda Solutions
Data Engineers Databricks / PySpark - Full Remote
Zurich, CHOn-siteContractFull-time
Posted Aug 24, 2026
This is a remote position.
We're hiring: Data Engineer (Freelance / Contract) – Remote
Remote | Time & Material | International enterprise environment
For our client, an enternational organization, we're looking for two experienced Data Engineers to join an IT Service Engineering team within a large international enterprise, supporting critical data engineering activities and ensuring continuity and knowledge transfer.
This position is full remote based.
Tasks and Responsibilities :
- Understand data-related dependencies, processes, system interactions, and source-of-truth concepts
- Identify and trace data flows across multiple source and target systems
- Investigate issues across system interfaces, data pipelines, and downstream processes to determine root cause
- Use Databricks and SQL for data analysis, assumption validation, inconsistency detection, and incident resolution
- Maintain and improve reliable data pipelines: validation, reconciliation, monitoring, documentation
- Work within established version-control, deployment, change, and release procedures
- Collaborate in an agile delivery environment, owning tasks end-to-end
Requirements
- Proven experience designing, developing, testing, and operating production-grade ETL/ELT pipelines
- Hands-on experience with Databricks, Python/PySpark, and SQL
- Experience integrating and reconciling data across enterprise systems (REST APIs, ITSM, ITFM, CMDB, IAM, ERP, monitoring, or similar)
- Experience with data validation, quality checks, reconciliation, monitoring, lineage, and schema evolution
- Git-based version control, code reviews, automated testing, CI/CD or comparable practices
- Experience with DEV/TEST/PROD environments and structured release/change processes
- Strong root-cause analysis skills across interfaces, pipelines, and downstream systems
- Fluent English
Role snapshot
Job type
Full-time
Required skills
DatabricksPython / PySparkSQLDesigning, developing, testing and operating production-grade ETL/ELT pipelinesIntegration with enterprise systems (REST APIs, ITSM, ITFM, CMDB, IAM, ERP)Data validation, quality checks, reconciliation, monitoring, lineage and schema evolutionGit-based version control and code review practicesAutomated testing and CI/CD practicesRelease/change management across DEV/TEST/PROD environmentsRoot-cause analysis across interfaces, data pipelines and downstream systemsAgile delivery and end-to-end task ownershipIncident investigation and resolutionDocumentation and knowledge transferFluent English
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