As an Azure Data Engineer you will collect, aggregate, store, and reconcile data in support of Client business decisions. You will help design and build data pipelines, data streams, reporting tools, information dashboards, data service APIs, data generators and other end-user information portals and insight tools. You will be a critical part of the data supply chain, ensuring that stakeholders can access and manipulate data for routine and ad hoc analysis to drive business outcomes using Advanced Analytics
Key Role Responsibilities:
Day-to-day, you will:
• Translate business requirements to technical solutions leveraging strong business acumen.
• Analyzes 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 PowerBI, Azure API Apps or any other modern visualization platform or experience.
• Implement effective metrics and monitoring processes.
Able to travel approximately 80%
- Key Role Skill & Capability Requirements:Your technical/non-technical skills include:• Demonstrated experience of turning business use cases and requirements to technical solutions.• Experience in business processing mapping of data and analytics solutions.• Ability to conduct data profiling, cataloging, and mapping for technical design and construction of technical data flows.• 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.• T-SQL is required.• Knowledge of Azure Data Factory, Azure Data Lake, Azure SQL DW, and Azure SQL, Azure App Service is required.• Azure HDInsight + Spark, Azure Cosmos DB, Azure Databricks, Azure Stream Analytics is a plus.• Knowledge of Python is a plus.• Experience preparing data for Data Science and Machine Learning.• Demonstrated experience preparing data and building data pipelines for AI Use Cases (text, voice, image, etc.…) is a plus.• Designing and building Data Pipelines using streams of IOT data is a plus.• Knowledge of Lambda and Kappa architecture patterns.• Knowledge of Master Data Management (MDM) and Data Quality tools and processes• Strong team collaboration and experience working with remote teams.• Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code fundamentals.• Working experience with Visual Studio, PowerShell Scripting, and ARM templates.• Experience with Git/TFS/VSTS is a must.Preferred Certifications: MCSAPreferred Education Background:You likely possess a Bachelor's degree in Computer Science, Information Technology, Business, or another relevant field. An equivalent combination of education and experience will also suffice.Preferred Years of Work Experience:You likely have about 3-5+ years of relevant professional experience.Scope of Work:Nature of Work: Executes project/program plans and processes in alignment with established operational objectives.Scope of Work: Primarily focused on own work, and execution of prescribed work plans.Complexity: Complex problems primarily within one's occupation / discipline that require personal judgement of contextual factors.Discretion: Wide latitude in approach to work within established work plans.Organizational Impact: Work efforts have an immediate impact on Avanade and/or client operations.Supervision Received: Works under general guidance and direction, but fully independent in own work with latitude for autonomous decision-making related to work process.Supervision Provided: Supports more junior colleagues on work efforts, with some checking of work.Knowledge Applied: Applies advanced knowledge of a learned occupation / discipline.