Senior Data Engineer
Tasks
- Build RAG and vector based data pipelines
- Build batch streaming and near real time pipelines
- Create and optimize data models
- Deliver datasets for analytics machine learning and causal modeling
- Design data platforms and pipelines
- Enable data governance security lineage and access control
- Establish data observability and monitoring
- Implement lakehouse patterns and medallion layering
- Monitor and optimize pipeline performance scalability and cost
- Orchestrate data workflows with scheduling automation
- Provide data serving layers via APIs and feature inputs
Perks/Benefits
- Career advancement and international mobility
- Growth framework
- Internal workshops and learning initiatives
- Learning and development
- Maternity and paternity leave support
- Medical insurance
- Mentoring program
- Multikafeteria
- Multisport card
- National holidays covered
- Paid vacation
- Professional Certification Reimbursement
- Remote and hybrid work options
- Sick leave
- Unpaid leave
Skills/Tech-stack
ABAC | AWS CloudFormation | Airflow | Amazon Web Services | Apache Spark | Azure Data | Azure Data Factory | Azure Resource | Azure Resource Manager | CI/CD | Cloud platform | DBT | Data Factory | Data Governance | Data Lineage | Data Modeling | Data Observability | Data Quality | Databricks | Delta Lake | Event Driven | Event-driven architecture | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kafka | LLMs | Lakehouse | Microsoft Azure | Microsoft Fabric | Python | RAG | RBAC | Resource manager | SQL | Snowflake | Streaming Architecture | Terraform | Vector Databases | Web Services | “as-code”
Education
N/A
Roles
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