Data Engineer
Tasks
- Apply infrastructure as code
- Build and optimize SQL data models
- Build data assets for downstream consumption
- Build enterprise data pipelines
- Capture transform and store data
- Design batch and streaming data solutions
- Develop data presentations using joins and aggregations
- Implement CI/CD pipelines
- Implement cloud data platforms
- Implement data streaming with Kafka
- Onboard data sources
- Optimize storage and query performance
- Run automated testing
- Set up and administer Tableau Server
- Set up configure and administer Databricks
- Set up configure and administer Snowflake
- Set up serverless computing services
- Use code version control
- Use containerisation technologies
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Glue | AWS RDS | AWS Redshift | AWS S3 | Automated testing | Azure | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Synapse | Azure Synapse Analytics | C# | CI/CD | Cloud Storage | Cosmos DB | Data Factory | Data Lake Storage | DataStreaming | Databricks | Docker | GCP | Google BigQuery | Google Bigtable | Google Cloud | Google Cloud Storage | Google Dataflow | Infrastructure as Code | Kafka | Python | SQL | Serverless | Snowflake | Synapse Analytics | Tableau Server | Version control | “as-code”
Education
N/A
Roles
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