Data Engineer IV
Tasks
- Automate data platform operations
- Build ingestion frameworks
- Create ETL ELT transformations
- Design cloud data pipelines
- Develop data integration solutions
- Establish engineering best practices
- Evaluate emerging technologies
- Implement data architecture
- Implement infrastructure-as-code
- Improve data quality and metadata management
- Mentor data engineers
- Model data for analytics
- Recommend platform improvements
- Set up CI/CD pipelines
- Support data governance
- Troubleshoot data platform issues
Perks/Benefits
Skills/Tech-stack
AWS | AWS AppFlow | AWS Glue | AWS Step Functions | Amazon Lake Formation | Amazon Redshift | Amazon S3 | Anomaly Detection | Apache Iceberg | Automated data quality | Azure DevOps | CI/CD | Contextual Layer | Data Governance | Data Lakehouse | Data Modeling | Data Quality | Data Warehousing | DevOps | Dimensional Modeling | ELT | ETL | Git | Infrastructure as Code | Lake Formation | Machine Learning | Metadata Management | Netsuite | Parquet | PySpark | Python | SQL | Salesforce | Semantic layer | Step Functions | Terraform | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Bachelor of Science in Computer Science | Bachelor of Science in Information Technology
Roles
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