Mid/Senior Data Engineer (Risk and Finance Reporting)

Tasks

• Build data architectures
• Build data processing systems
• Collaborate with analysts and stakeholders
• Design data ingestion systems
• Develop ELT pipelines
• Develop ETL pipelines
• Develop data storage solutions
• Ensure data performance
• Ensure data quality
• Ensure data security
• Ensure system availability
• Fix defects
• Implement data sharing
• Implement monitoring and alerting
• Integrate systems data flows
• Optimize data pipeline performance
• Perform code reviews
• Support agile development
• Troubleshoot software defects

Perks/Benefits

• Extra vacation
• Flexible working hours
• Health days
• Health insurance
• Hybrid work
• Paid leave
• Special discounts
• Training and development
• Volunteer time off
• Wellbeing programs

Skills/Tech-stack

AWS | Amazon Redshift | Apache Airflow | Apache Flink | Apache Kafka | Apache Spark | Azure | CI/CD | Cloud platform | DBT | Docker | ELT | ETL | Event Driven | Event-driven architecture | Google BigQuery | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubernetes | Message-based | Message-based integration | NoSQL | Python | Real Time | Real-time integration | SQL | Snowflake | Test automation | Time integration | “as-code”