Data Engineer
Tasks
- Build manage optimize data pipelines
- Create maintain SQL data models stored procedures views
- Design implement data ingestion transformation validation delivery
- Design, develop, maintain ETL/ELT pipelines
- Implement data quality checks validation logging alerting
- Implement data transformation logic
- Modernize migrate legacy ETL from SSIS to cloud
- Receive organize load data to data warehouse
- Support client onboarding data ingestion transformation reconciliation
- Translate business requirements into data solutions
- Troubleshoot data pipeline data quality performance issues
Perks/Benefits
- Community outreach volunteering
- Employee resource groups
- Flexible PTO
- Professional mentoring
- Training and development
- Work from home
Skills/Tech-stack
Alerting | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Databricks | Azure Databricks notebooks | Azure Key Vault | Azure Storage | Azure Storage Accounts | Data Factory | Data Lake Storage | Data Quality | Data Validation | Data pipeline | Data pipeline orchestration | Databricks Notebooks | ELT | ETL | Fabric notebooks | Key Vault | Logging | Microsoft Fabric | Microsoft Fabric Notebooks | Monitoring | Pipeline Orchestration | Power BI | PySpark | Python | Reconciliation | SQL | SQL Indexing | SQL stored procedures | SQL views | Semantic models | Spark SQL | Storage Accounts | Stored Procedures | T-SQL
Roles
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