M19 - Data Engineer
Tasks
- Build and maintain Databricks based analytics platforms
- Build data ingestion and transformation workflows
- Collaborate with business users analysts and architects
- Design data models and maintain data architecture
- Design scalable ETL/ELT data pipelines
- Develop and optimize data warehouses and data lakes
- Develop batch and real-time processing solutions
- Develop solutions on AWS Azure or GCP
- Ensure data quality, consistency, and reliability
- Implement data transformation and modeling best practices
- Integrate enterprise systems and APIs
- Optimize platform performance scalability and cost
- Participate in Agile project delivery
- Prepare and deliver data for analytics and business intelligence
- Prepare technical documentation and maintain standards
- Provide troubleshooting and production support
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Azure | Azure Data | Azure Data Factory | CI/CD | Cloud platform | Data Factory | Data Governance | Data Lakes | Data Modeling | Data Processing | Data Quality | Data Transformation | Data Warehousing | Databricks | ELT | ETL | Google Cloud | Google Cloud Platform | Infrastructure automation | Java | Python | Real Time | Real-time Data | Real-time Data Processing | SQL | Scala
Education
Roles
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