Data Engineer
Tasks
- Apply data modeling and schema design best practices
- Design and maintain batch and streaming data pipelines
- Develop cloud-based data solutions
- Document data pipelines and architectures
- Ensure compliance with data privacy legislation POPA
- Ensure data quality, reliability, and performance
- Implement data integration and ETL/ELT processes
- Implement data versioning migration and change management
- Manage and optimize data lake warehouse and lakehouse architectures
- Monitor pipelines with alerting and logging
- Support data governance privacy security and ethical use
- Translate requirements into scalable data solutions
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Glue | Airflow | Amazon Kinesis | Avro | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Event | Azure Event Hubs | Azure Synapse | Azure Synapse Analytics | CI/CD | Change Management | CloudFormation | Data Factory | Data Governance | Data Lake | Data Lake Storage | Data Modeling | Data Observability | Data Pipeline Monitoring | Data Privacy | Data Quality | Data Security | Data Validation | Data Versioning | Data Warehouse | Data pipeline | Databricks | Delta Lake | ELT | ETL | Event Hubs | Infrastructure as Code | JSON | Java | Kafka | Lakehouse | Parquet | Pipeline monitoring | Python | Redshift | S3 | SQL | Scala | Schema Design | Spark | Step Functions | Synapse Analytics | Terraform | XML | “as-code”
Education
Associate Degree | Bachelor of Arts | Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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