Azure Data Architect

Key Requirements

• 5+ years' experience leading engagements from design to implementation of creative data solutions leveraging the latest in Spark based modern data platforms on public cloud
• At least 2 full lifecycle data platform deployments on Azure using first party services for Data and Analytics.
• Extensive experience with following technologies; Azure Data Factory, Azure Synapse Analytics, Azure Databricks,
• Extensive experience of Azure foundation and cloud engineering concepts including network, security, cost estimation, common IaaS and PaaS services and monitoring.
• Strong Spark, SQL, Data Modeling, Data lakehouse concepts.
• Programming / scripting experience using python and scala.
• 5+ years' experience architecting solutions for optimal extraction, transformation and loading of data from a wide variety of traditional and non-traditional sources such as structured, unstructured, and semi-structured using SQL, NoSQL and data pipelines for real-time, streaming, batch and on-demand workloads 
• 3+ years' experience with analytics/data management strategy formulation, architectural blueprinting and effort estimation of analytics 
• 3+ years working in cloud or multi-server complex environments.  Extensive experience with Azure is required.
• Ability to simplify complex technical concepts into an easy-to-understand non-technical language to facilitate, communicate and interact with executives and business stakeholders 
• Ability to deal with ambiguity by making the appropriate decisions considering the relative costs and benefits of potential actions.  
• Experience with Agile development methods in data-oriented projects 
• Experience with Dashboarding and Reporting Tools used in the industry (Tableau, Power BI, Qlik, etc.) 
• Certifications in architecture, data engineering and development from Azure is preferred
• Knowledge of software configuration management environments and tools such as JIRA, Git, Jenkins, TFS, Shell, PowerShell, Bitbucket.

Data Specialisation

• Lead, define and implement end-to-end modern data platforms on public cloud using 1st party services in support of analytics and AI use cases 
• Collaborate with enterprise architects, data architects, ETL developers & engineers, data scientists, and information designers to lead identification and definition of required data structures, formats, pipelines, metadata, and workload orchestration capabilities 
• Address aspects such as data privacy & security, data ingestion & processing, data storage & compute, analytical & operational consumption, data modeling, data virtualization, self-service data preparation & analytics, AI enablement, and API integrations 
• Be the technical liaison between customers and engineering teams 
• Be a big data evangelist by educating a variety of customers on the value of cloud and data services 

General Consultancy

• Present recommendations to clients using both written deliverables and face-to-face discussions 
• Develop deep relationships with clients and act as the single point of contact for client executives on data engagements 
• Directly collaborate with the sales team to formulate and execute a sales strategy to facilitate the adoption of Azure data offerings.
• Lead the professional services elements of relevant data proposals and RFP/RFI responses, including scope, effort, pricing models and SOW development.  
• Guide customers during big data and cloud adoption by: 
• Understanding drivers of technology change 
• Building business cases to undertake technology change 
• Lead discovery sessions with stakeholders, including - interviews, document analysis, requirements workshops, surveys, client on-site visits, business process descriptions, use cases, scenarios, and data analysis for technology change 
• Identify gaps in customer maturity and capabilities in relation to their data strategy. 
• Identify areas of opportunity, and recommend future state improvements  
• Work with Engagement / Project Managers to plan the delivery of data projects, including budget, delivery resources, partner engagement, schedules and responsibilities. 
• Accountable for the successful outcome of data and related engagements from both a delivery (schedule, deliverables etc.) and commercial (revenue realization, budget etc.) perspective. 
• Lead the effort to find creative approaches to problem solving and identify, mitigate, or escalate delivery risks and issues.
• Based In Germany
• #LI-JB2
• #LI-Remote