Digital Factory - Data Engineer - Assistant Director
EUR 75K-107K (estimate) Executive-level Full Time
Tasks
- Build reusable data engineering frameworks
- Define and evolve data engineering standards and guardrails
- Define and govern SLAs and SLOs for data assets
- Define data engineering strategy and roadmap
- Define data quality reliability and observability standards
- Design and implement batch and streaming data pipelines
- Design data platform target architecture
- Design for scalability resilience and fault tolerance
- Ensure compliance with regulatory and privacy obligations
- Ensure data ingestion transformation and serving layers
- Establish and govern data contracts schemas and versioning
- Explain technical trade offs risks and investment needs
- Govern architecture decisions
- Hold accountability for production data platform stability and availability
- Implement unit integration data quality and regression testing
- Lead incident management and root cause analysis
- Optimize compute storage and query performance and costs
- Own data engineering outcomes end to end
- Own secure by design data engineering practices access controls and encryption
- Provide technical leadership, mentoring, and coaching
- Reduce operational risk through automation and standardization
- Represent data engineering in audits and risk assessments
- Set engineering quality and delivery standards
- Support capacity planning skill development and succession planning
- Translate stakeholder objectives into data solutions
Perks/Benefits
- Career development and training
- Diverse and inclusive culture
- Flexible work environment
- Global team collaboration
Skills/Tech-stack
Access Control | Airflow | Automated testing | Azure | Azure Data | Azure Data Factory | Azure Event | Azure Event Hubs | Backpressure | Batch Processing | Bicep | CI/CD | Cause analysis | Checkpointing | Code Quality | DBT | Data Contracts | Data Engineering | Data Factory | Data Governance | Data Modeling | Data Pipelines | Data Quality | Data Quality Testing | Data Warehouse | Databricks | Dimensional Modeling | Encryption | Engineering governance | Event Hubs | Idempotency | Incident Management | Infrastructure as Code | Integration Testing | Kafka | Lakehouse | Normalization | Observability | Python | Quality testing | Regression testing | Retries | Root Cause Analysis | Root cause | SQL | Schema versioning | Secrets management | Service Bus | Spark | Streaming | Terraform | Unit Testing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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