Mid-Level Data Engineer
Tasks
- Apply data validation rules
- Apply security privacy compliance requirements
- Automate operational tasks
- Build data transformation logic
- Collaborate with data governance security compliance teams
- Create data ingestion processes
- Create unit tests
- Develop Spark workloads
- Develop data pipelines
- Ensure data contracts compliance
- Follow coding and engineering standards
- Implement schema mappings
- Investigate data quality issues
- Maintain data classification information
- Maintain data schemas
- Manage metadata and documentation
- Monitor pipeline workflows
- Participate in code reviews
- Perform data quality checks
- Set up alerting and incident support
- Support auditability documentation metadata lineage
- Support data lineage activities
- Troubleshoot pipeline failures
- Validate transformations
- Write Python scripts
- Write SQL queries
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Access Management | Apache Spark | Authentication | Authorization | Automation | Azure | Data Governance | Data Lineage | Data Quality | Data Transformation | Data Validation | Data Warehousing | Databricks | ELT | ETL | Git | Google Cloud | Least Privilege | Metadata Management | Python | Relational databases | SQL | Secrets management | Version control
Education
Associate Degree | Bachelor of Engineering | Bachelor of Engineering in Computer Engineering | Bachelor of Science | Bachelor of Science in Computer Science | Master of Science
Roles
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