Lead the design and conception of mission-critical data architectures.
Translate complex business requirements into cutting-edge technological solutions.
Lead the technical definition of projects.
Estimate cloud infrastructure effort and costs.
Ensure adoption of new data technologies delivers maximum efficiency, scalability and satisfaction to internal stakeholders.
Requirements
Databricks and Azure ecosystem: Experience in Big Data architecture using Databricks (Lakehouse, Unity Catalog) and the Azure stack (Data Factory, Synapse Analytics and Microsoft Fabric).
Engineering and Distributed Processing: Experience with Python, SQL and PySpark, with an understanding of Spark distributed architecture.
Architecture and Estimation: Proficiency in designing scalable data architectures and estimating development effort and cloud costs (Azure calculator); able to design infrastructure cost models and optimize workloads.
Traditional BI Background (Microsoft Stack): Solid experience with SQL Server, SSIS and SSAS to understand legacy systems and ensure safe integrations or migrations to the cloud.
Data Visualization: Knowledge of data architecture and modeling to design integrated data visualizations and consolidated data solutions.
Data Modeling and Databases: Fluency operating between relational and non-relational (NoSQL) environments, ensuring the appropriate model for each use case.
Agile Methodologies: Familiarity with Agile ceremonies (Scrum or Kanban), including metrics, backlog refinement and crafting user-story narratives and tasks related to your activities.
Experience integrating and extracting data from the SAP ecosystem (BW, BODS, BDC or DataSphere) into cloud Data Lake/Data Warehouse environments.