Welcome to Sansaone, a dynamic force in the realm of ICT talent acquisition. Born out of a passion for excellence and a vision for connecting outstanding professionals with forward-thinking organizations, we stand as a beacon for strategic recruitment solutions in the Information and Communication Technology sector. With a commitment to excellence and a passion for connecting exceptional professionals with innovative organizations, we are your strategic partner in building transformative teams.
Responsibility
Design, develop, document, and maintain ETL/ELT processes, data integration, cleaning, transformation, dissemination and automation processes.
Create robust solutions to collect, integrate, and process structured, semi-structured, and unstructured data (e.g. JSON, Parquet, Delta).
Design, develop, document and maintain data architecture, data modelling and metadata.
Develop and support data warehouse/lakehouse architectures and data processing ensuring data quality, lineage, auditing, metadata, logging, linkage across datasets and impact assessments.
Work collaboratively with data providers to address data gaps and optimize source-system structures.
Develop and maintain business intelligence models, interactive dashboards, reports and analytics using tools such as Databricks, Jupyter Notebooks, and Power BI.
Design, develop, document, improve and maintain the Data Warehouse/Lakehouse ecosystem (e.g. the DataDevOps lifecycle, architecture).
Support the gathering and analysis of business requirements, translating them into scalable data collection and integration processes.
Contribute to the definition and documentation of data governance policies, procedures, standards, and metadata models.
Participate in meetings with project and data teams to align on strategic priorities, ensuring seamless integration and optimal data management practices.
Requirements
Have a minimum a High School diploma.
At least 6 years of professional experience.
Proficiency in data development and processing using Python, SQL, Power M, and DAX.
Experience working with structured, semi-structured, and unstructured data types and file formats (e.g., JSON, Parquet, Delta).
Ability to gather and translate business requirements into scalable data collection, integration, and analysis processes.
Hands-on experience with Microsoft On-Premise and Azure Data Platform tools, including: Azure Data Factory, Azure Functions, Azure Logic Apps, SQL Server, Azure Data Lake Storage (ADLS), Azure Databricks, Microsoft Fabric/Power BI, Azure DevOps, Azure AI Services, PowerShell).
Familiarity with CI/CD workflows, particularly using Azure DevOps.
Strong knowledge of the Databricks ecosystem, Apache Spark, and Python data libraries.
Solid understanding of data modeling principles and techniques.
Experience with Data Lakes and Lakehouse architectures, including governance and lifecycle management.
Knowledge of data integration and data warehouse/lakehouse modeling techniques, such as: Slowly Changing Dimensions (SCD), Functional engineering, Data Vault, Data streaming.
Understanding of data governance and data management standards, including metadata, data quality, policies, and compliance.
Familiarity with Web APIs and the OpenAPI specification.
Proficiency in English language at a minimum B2 level.
