Data Engineer, Senior (Hybrid)
Tasks
- Design, build, and maintain data pipelines
- Drive incident management and root cause analysis
- Implement automated testing validation and monitoring for data workflows
- Integrate DevSecOps security automation and quality controls
- Manage cloud configuration changes for data reliability
- Mentor engineers through code reviews and knowledge sharing
- Monitor tune and optimize data pipeline performance and reliability
- Provide sustaining support for cloud data platforms
- Translate functional requirements into technical designs
Perks/Benefits
Skills/Tech-stack
Apache Airflow | Automated testing | Azure | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Synapse | Azure Synapse Analytics | Bitbucket | CI/CD | Cause analysis | DBT | Data Architecture | Data Factory | Data Governance | Data Lake Storage | Data Modeling | Data Quality | Data Vault | Data Vault 2.0 | Data Warehousing | Data integration | Databricks | DevSecOps | GitHub | Monitoring | Root Cause Analysis | Root cause | SQL | Snowflake | Synapse Analytics
Education
N/A
Roles
Regions
Countries
States
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