Data Engineer
Tasks
- Design and evolve scalable data architectures
- Develop and optimize ETL and ELT pipelines
- Ensure data validation documentation and best practices
- Implement AI and ML based data cleansing normalization deduplication and enrichment
- Implement and optimize data integration processes
- Implement data quality and data governance mechanisms including GDPR compliance
- Lead requirements gathering and solution design
- Manage and optimize client databases performance integrity and security
- Mentor and guide data engineers
- Monitor data pipelines resolve incidents and drive continuous improvement
- Provide knowledge transfer and training to teams and clients
Perks/Benefits
- Childcare support
- Discounts on physiotherapy and gyms
- Employee wellness program
- Financial support service
- Flexible hours
- Health insurance
- Hybrid work
- Legal support service
- Meals support
- Permanent contract
- Remote during holidays
- Transportation support
- Vacation days
- Work-life balance support
Skills/Tech-stack
AI Algorithms | AKS | Apache Airflow | Azure | Azure Data | Azure Data Factory | Azure Event | Azure Event Hubs | Azure Functions | CI/CD | Cloud Run | Cloud platform | Customer Data | Customer Data Platform | Data Factory | Data Governance | Data Modeling | Data Normalization | Data Quality | Data Security | Data Warehousing | Data orchestration | Data platform | DataOps | Dimensional Modeling | Docker | ELT | ETL | Event Hubs | GDPR | GKE | Google Cloud | Google Cloud Platform | GraphQL | JavaScript | Kafka | Kubernetes | MLOps | Machine Learning | Microservices | MuleSoft | NoSQL | Node.js | PLSQL | Pentaho | PubSub | Python | Query Optimization | REST APIs | Relational databases | SQL | Salesforce | Segment | Serverless computing | Snowflake | Stored Procedures | TSQL
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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