What makes you a great fit:

• Translate business requirements to technical solutions leveraging strong business acumen
• Analyse current business practices, processes and procedures as well as identifying future business opportunities for leveraging Microsoft Azure Data & Analytics PaaS Services
• Support the planning and implementation of data design services, providing sizing and configuration assistance and performing needs assessments.
• Delivery of architectures for transformations and modernizations of enterprise data solutions using Azure cloud data technologies.
• Design and Build Modern Data Pipelines and Data Streams.
• Design and Build Data Service APIs.
• Develop and maintain data warehouse schematics, layouts, architectures and relational/non-relational databases for data access and Advanced Analytics.
• Expose data to end users using Power BI, Azure API Apps or any other modern visualization platform or experience.
• Implement effective metrics and monitoring processes.Skill & Capability Requirements:
• 5+ years of working experience as a Data Engineer
• Demonstrated experience in turning business use cases and requirements into technical solutions.
• Experience in business processing mapping of data and analytics solutions.
• The ability to apply such methods to solve business problems using one or more Azure Data and Analytics services in combination with building data pipelines, data streams, and system integration.
• Ability to leverage a variety of programming languages & data crawling/processing tools to ensure data reliability, quality & efficiency.
• Experienced in Cloud Data Transformation using ETL/ELT tools such as Azure Data Factory, Azure Synapse Analytics, Databricks
• Experienced in writing well-versed SQL scripts/Stored Procedures to achieve desired transformation.
• Experienced in Dev-Ops processes (including CI/CD) and Infrastructure as code fundamentals.
• Knowledge of business intelligence tools such as Power BI, Tableau, Qlik, Cognos TM1
• Knowledge of Azure Data Lake, Azure SQL DW, and Azure SQL, Azure App Service is required.
• Knowledge in data modelling and database management, such as performance tuning of the Enterprise Data Warehouse, Data Mart, and Business Intelligence Reporting environments, and support the integration of those systems with other applications.
• Knowledge of Python is a plus.
• Experience preparing data for Data Science and Machine Learning.
• Experience preparing data for use in Azure Machine Learning / Azure Databricks is a plus.
• Experience preparing data and building data pipelines for AI Use Cases (text, voice, image, etc).
• Strong team collaboration and experience working with remote teams.
• Azure certifications (AZ-900, AZ-200, and 201), Databricks certification, DevOps certifications are plus.