Data Engineer
Company on Finance industry
Catania
20
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Azienda: Company on Finance industry Catania
This project aims to centralize and streamline the company’s data architecture, enabling efficient and secure data integration, storage, and analytics within the Azure environment.
Project Objectives: Develop and Optimize Data Pipelines: Design, develop, and implement data pipelines within the Azure environment to streamline data ingestion, transformation, and loading processes.
Ensure pipelines are highly performant and can handle large data volumes across multiple sources.
Data Warehouse and Analytics Development: Support the development and maintenance of a centralized data warehouse in Azure, utilizing Azure Analysis Services and Databricks.
This will enable seamless access to curated data for analytics and business intelligence.
Integrate Data with Business Intelligence Tools: Facilitate data accessibility and reporting by integrating curated data into Power BI, allowing business stakeholders to generate meaningful insights and improve decision-making processes.
Enhance Data Quality and Governance: Implement data validation and monitoring processes to ensure data accuracy, consistency, and integrity throughout the pipeline.
Work with data governance teams to apply best practices and standards for data quality and security.
Collaborate on a Scalable Data Architecture: Collaborate closely with cross-functional teams to design a data architecture that can scale with the organization’s future data and analytical needs.
Main requirements Project Deliverables: Functional Data Pipelines in Azure : Fully operational data pipelines developed in Azure using Databricks and Py Spark (if necessary), capable of processing and transforming high volumes of data from multiple sources.
Centralized Data Warehouse : A fully integrated data warehouse in Azure Analysis Services that provides a consolidated view of organizational data, facilitating analytics and reporting.
Power BI Dashboards and Reports : A suite of Power BI dashboards and reports providing relevant metrics, insights, and data visualizations tailored to business stakeholder needs.
Documentation and Best Practices Guide : Comprehensive documentation for all data pipelines, data models, and workflows, along with a best practices guide on data integration, transformation, and security in Azure.
Data Quality and Monitoring Framework : A framework to monitor data quality across all stages of the data lifecycle, including data validation checks and error handling processes.
The candidate’s ability to communicate effectively in English, their remote working capability, and the potential for a long-term engagement will be crucial for continuity and alignment with team goals.
✔ Company on Finance industry