Data Engineer
Tasks
- Build and maintain ETL/ELT pipelines
- Collaborate on data model implementation
- Develop batch and real time data processing workflows
- Ensure low latency data availability where required
- Implement data transformation logic
- Implement data validation, monitoring, and alerting
- Ingest data from internal systems and external APIs
- Integrate transactional and API driven data sources
- Model structured data layers for analytics
- Optimize pipeline performance and cost
- Resolve data inconsistencies and pipeline failures
- Scale data infrastructure as volumes grow
- Support analytics teams with curated datasets
Perks/Benefits
- Employee assistance program
- Flexible core hours
- Hybrid working
- Life assurance
- Local discounts
- Paid holiday
- Pension
- Private medical insurance
- Team building opportunities
- Wellness allowance
Skills/Tech-stack
API | Apache Airflow | Apache Kafka | CI/CD | DBT | Data Modeling | Data Processing | Data Transformation | Data Validation | Data Warehousing | ELT | ETL | Event Streaming | Event ordering | Idempotency | Infrastructure as Code | Monitoring | Python | Real Time | Real-time Data | Real-time Data Processing | SQL | Workflow Orchestration | “as-code”
Education
N/A
Roles
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