We are looking for a Senior Azure Data Integration Engineer to design, build, and scale enterprise-grade data integration solutions on Azure. This role is ideal for someone who thrives in complex environments, integrating multiple data sources (network, asset, HR, and location data) into robust, scalable reporting models that power business-critical insights.
You will play a key role in supporting production data pipelines, ensuring high data quality, and collaborating across enterprise teams to deliver end-to-end data solutions.
Key Responsibilities
- Design, build, and maintain Azure-based data integration pipelines using Azure Data Factory, Databricks, and related services
- Integrate diverse enterprise data sources (network telemetry, asset management, HR systems, location data, and badge access systems) into unified data models
- Develop and optimize data pipelines in Python and Spark SQL
- Support production data pipelines, troubleshooting issues and implementing performance improvements
- Perform data validation, reconciliation, and quality assurance checks
- Create and maintain source-to-target mappings and technical documentation
- Implement and maintain medallion/layered data architectures in Azure Data Lake
- Collaborate with cross-functional teams, including HR, network, asset management, and reporting teams
- Prepare datasets for Power BI reporting and analytics
- Drive identity resolution and data reconciliation across multiple enterprise systems
- Contribute to enterprise data governance and best practices
- Support enterprise-scale reporting platforms from pilot to global rollout and operational transition
Required Skills & Experience
- Strong hands-on experience with:
- Azure Data Factory
- SQL
- REST API ingestion
- Azure Data Lake Storage
- Proven experience in:
- Data integration and troubleshooting in complex enterprise environments
- Building scalable data models integrating multiple data domains
- Supporting production-grade data pipelines
- Data quality validation and reconciliation
- Source-to-target mapping and documentation
- Ability to work effectively across multiple enterprise teams
- Python, Databricks, Spark SQL
- Understanding of medallion/layered data architecture
- Experience withenterprisedatasets such as:
- Asset management / AMDB / CMDB / TBM
- HR systems (e.g., Employee Central)
- Identity resolution and multi-system reconciliation
- Knowledge of:
- Badge access systems (e.g., ProWatch)
- Workplace or physical presence data
- Experience integrating:
- Network telemetry
- Asset management
- HR and location data into enterprise reporting
- Familiarity with Power BI dataset preparation
- Exposure to enterprise data governance frameworks
- Experience supporting enterprise-scale data/reporting platforms from implementation to global rollout
Interested Please apply and let's connect!
Razvan Tarus
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