Data Engineer | Product Developer
Tasks
- Contribute to DevOps initiatives and technical documentation
- Create technical documentation standards and best practices
- Design and maintain data models for reporting controls and auditability
- Design data pipelines for payroll data processing and automation
- Develop and optimize data ingestion transformation and validation processes
- Implement data quality checks reconciliation rules and audit logging
- Improve platform performance reliability monitoring and maintainability
- Integrate data from APIs flat files payroll providers and client systems
- Manage and enhance Data Lake and Delta Lake environments
- Participate in architecture discussions and code reviews
- Support testing, deployment, and release activities
- Troubleshoot data pipeline issues performance bottlenecks and data inconsistencies
- Use Azure services to deliver scalable and reliable data solutions
Perks/Benefits
Skills/Tech-stack
Apache Spark | Audit Logging | Automated testing | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Databricks | Azure SQL | Azure SQL Database | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Factory | Data Lake | Data Lake Architecture | Data Lake Storage | Data Modeling | Data Pipeline Monitoring | Data Quality | Data Validation | Data pipeline | Data platform | Data platforms | Delta Lake | Git | Infrastructure as Code | Layered Data Platform | Metadata Driven | Metadata Driven Frameworks | Multi-tenant | Multi-tenant data platforms | Performance optimization | Pipeline monitoring | Power BI | Python | REST APIs | Reconciliation | SQL | SQL Database | Semantic Modeling | Synapse Analytics | “as-code”
Education
N/A
Roles
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