Enterprise Lead Data Engineer
Tasks
- Automate data acquisition cleansing validation transformation
- Build Microsoft Fabric lakehouse and warehouse solutions
- Build data models for ERP CRM Power Platform
- Build integrations using APIs connectors files database extracts
- Create monitoring and alerting for pipeline health and data quality
- Design and support stored procedures notebooks scripts automation
- Design data domains and naming conventions lineage metadata
- Design enterprise data platform
- Develop ETL and ELT pipelines
- Develop data architecture standards
- Develop ingestion transformation orchestration frameworks
- Establish data quality standards validation remediation
- Implement data lineage catalog metadata documentation
- Implement ingestion transformation storage governance security
- Implement medallion architecture
- Lead Dynamics 365 Customer Engagement integration
- Lead Dynamics 365 Finance and Operations integration
- Maintain Dataverse ingestion and synchronization
- Optimize storage compute performance cost
- Support compliance privacy security access controls identity governance
- Troubleshoot production data pipeline failures
- Write SQL Python Spark transformation logic
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Automation | Azure Data | Azure Data Factory | Data Factory | Data Governance | Data Lineage | Data Management | Data Modeling | Data Pipeline Monitoring | Data Quality | Data Warehousing | Data pipeline | Dataflows Gen2 | Dataverse | ELT | ETL | JSON | Lakehouse | Master Data | Master Data Management | Medallion Architecture | Metadata | Microsoft Fabric | Notebooks | OneLake | Orchestration | Pipeline monitoring | Power Platform | Powershell | Python | REST API | SQL | Stored Procedures | Warehouse
Roles
Data Engineer | Engineer | Enterprise Data Engineer | Lead | Lead Data | Lead Data Engineer
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