- 24.08.2026
- 40 - 100%
- Poste à responsabilités
- Indépendent
Data Scientist x 2 (m,f,d) Python/PySpark
Data Scientist x 2 (m,f,d) Python/PySpark/SQL/Databricks 60 - 100% (Remote)
Project: We are looking for two experienced Data Engineers to support ongoing data engineering activities within an IT Service Engineering environment. The focus is on building and maintaining reliable data pipelines, tracing data across complex enterprise systems and resolving data and integration issues. The resources will also help ensure operational continuity and effective knowledge transfer within the team.
Tasks:
* Analyse data dependencies, processes, system interactions and source-of-truth concepts.
* Identify and trace data flows across multiple source and target systems.
* Investigate issues affecting system interfaces, data pipelines and downstream processes.
* Perform root-cause analysis and drive incidents through to resolution.
* Use Databricks, Python/PySpark and SQL for data analysis, validation and inconsistency detection.
* Develop, maintain and improve production-grade ETL/ELT data pipelines.
* Implement data validation, reconciliation, monitoring and quality controls.
* Follow established version-control, deployment, change and release procedures.
* Test, validate and document delivered solutions.
* Communicate findings, risks, dependencies and progress clearly to relevant stakeholders.
* Work collaboratively within an agile, cross-functional team and take ownership of assigned tasks.
Requirements:
* Proven experience designing, developing, testing and operating production-grade ETL/ELT data pipelines.
* Strong hands-on experience with Databricks or a comparable data platform.
* Strong practical experience with Python/PySpark and SQL.
* Experience integrating and reconciling data from multiple enterprise systems and REST APIs.
* Experience implementing data validation, quality checks, reconciliation, monitoring, lineage and schema evolution.
* Practical experience with Git, branching strategies, code reviews and automated testing.
* Experience with CI/CD and structured deployments across DEV, TEST and PROD environments.
* Strong root-cause analysis experience involving interfaces, pipelines and downstream processes.
* Experience working in agile, cross-functional teams.
* Strong communication skills with both technical and non-technical stakeholders.
* Fluent English (spoken and written)
Nice-to-Haves:
* Experience with ITSM, ITFM, CMDB, IAM, ERP or monitoring systems.
* Knowledge of service data, cost-transparency or IT financial management use cases.
Project: We are looking for two experienced Data Engineers to support ongoing data engineering activities within an IT Service Engineering environment. The focus is on building and maintaining reliable data pipelines, tracing data across complex enterprise systems and resolving data and integration issues. The resources will also help ensure operational continuity and effective knowledge transfer within the team.
Tasks:
* Analyse data dependencies, processes, system interactions and source-of-truth concepts.
* Identify and trace data flows across multiple source and target systems.
* Investigate issues affecting system interfaces, data pipelines and downstream processes.
* Perform root-cause analysis and drive incidents through to resolution.
* Use Databricks, Python/PySpark and SQL for data analysis, validation and inconsistency detection.
* Develop, maintain and improve production-grade ETL/ELT data pipelines.
* Implement data validation, reconciliation, monitoring and quality controls.
* Follow established version-control, deployment, change and release procedures.
* Test, validate and document delivered solutions.
* Communicate findings, risks, dependencies and progress clearly to relevant stakeholders.
* Work collaboratively within an agile, cross-functional team and take ownership of assigned tasks.
Requirements:
* Proven experience designing, developing, testing and operating production-grade ETL/ELT data pipelines.
* Strong hands-on experience with Databricks or a comparable data platform.
* Strong practical experience with Python/PySpark and SQL.
* Experience integrating and reconciling data from multiple enterprise systems and REST APIs.
* Experience implementing data validation, quality checks, reconciliation, monitoring, lineage and schema evolution.
* Practical experience with Git, branching strategies, code reviews and automated testing.
* Experience with CI/CD and structured deployments across DEV, TEST and PROD environments.
* Strong root-cause analysis experience involving interfaces, pipelines and downstream processes.
* Experience working in agile, cross-functional teams.
* Strong communication skills with both technical and non-technical stakeholders.
* Fluent English (spoken and written)
Nice-to-Haves:
* Experience with ITSM, ITFM, CMDB, IAM, ERP or monitoring systems.
* Knowledge of service data, cost-transparency or IT financial management use cases.
Data Scientist x 2 (m,f,d) Python/PySpark
Data Scientist x 2 (m,f,d) Python/PySpark/SQL/Databricks 60 - 100% (Remote)
Project: We are looking for two experienced Data Engineers to support ongoing data engineering activities within an IT Service Engineering environment. The focus is on building and maintaining reliable data pipelines, tracing data across complex enterprise systems and resolving data and integration issues. The resources will also help ensure operational continuity and effective knowledge transfer within the team.
Tasks:
- Analyse data dependencies, processes, system interactions and source-of-truth concepts.
- Identify and trace data flows across multiple source and target systems.
- Investigate issues affecting system interfaces, data pipelines and downstream processes.
- Perform root-cause analysis and drive incidents through to resolution.
- Use Databricks, Python/PySpark and SQL for data analysis, validation and inconsistency detection.
- Develop, maintain and improve production-grade ETL/ELT data pipelines.
- Implement data validation, reconciliation, monitoring and quality controls.
- Follow established version-control, deployment, change and release procedures.
- Test, validate and document delivered solutions.
- Communicate findings, risks, dependencies and progress clearly to relevant stakeholders.
- Work collaboratively within an agile, cross-functional team and take ownership of assigned tasks.
Requirements:
- Proven experience designing, developing, testing and operating production-grade ETL/ELT data pipelines.
- Strong hands-on experience with Databricks or a comparable data platform.
- Strong practical experience with Python/PySpark and SQL.
- Experience integrating and reconciling data from multiple enterprise systems and REST APIs.
- Experience implementing data validation, quality checks, reconciliation, monitoring, lineage and schema evolution.
- Practical experience with Git, branching strategies, code reviews and automated testing.
- Experience with CI/CD and structured deployments across DEV, TEST and PROD environments.
- Strong root-cause analysis experience involving interfaces, pipelines and downstream processes.
- Experience working in agile, cross-functional teams.
- Strong communication skills with both technical and non-technical stakeholders.
- Fluent English (spoken and written)
Nice-to-Haves:
- Experience with ITSM, ITFM, CMDB, IAM, ERP or monitoring systems.
- Knowledge of service data, cost-transparency or IT financial management use cases.
ReferenceNr.: 925177KS
Role: Data Scientists x 2 (all)
Location: Zürich / Remote
Workload: 60 -100 %
Start: ASAP
Duration: 31.03.2027 (With potential Extension)