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Microsoft Data & AI Technical Specialist - Major Growth 
United Kingdom, England, London 
331313522

09.07.2024

AI to address challenges and enhance achievements.You will

and use our technology.and develop your deep technical

Required/Minimum Qualifications (RQs/MQs)

  • Previous experience in technical pre-sales or technical consulting
  • Bachelor's or Master's Degree in Computer Science, Information Technology, or related field (or equivalent qualification) combined with technical pre-sales or technical consulting experience
  • with cloud and hybrid, or on premisesdatabaseinfrastructures, architecture designs, migrations, industry standards, and/or technology management.
  • Partners: Experienceleveraging
  • Proof of Concepts:Experience creatingDatabase, Analytics, and AI Proofof Concepts (PoC)/Pilots for customersthat lead to production deployments.

Additional or Preferred Qualifications (PQs)

  • Certification in relevant technologies or disciplines (e.g., Office 365, Power BI, Azure Architect and Development exams, Cloud Platform Technologies, Information Security, Architecture)
  • Azure Certifications:Azure Data Engineer Associate (DP 203) ororAzure AI Engineer Associate (AI-102) orEnterpriseData Analyst Associate (DP600) or Azure Cosmos DB Developer Specialty (DP 420)or Fabric Analytics Engineering Associate (DP- 600).
  • Knowledge ofCompetitiveDatabase platforms such as AWS, GCP, Mongo DB, and Oracle.Knowledge ofCompetitiveIntelligent Data and Analytics platforms such as Snowflake, Databricks, AWS (Redshift), GCP Big query, Teradata, Netezza, Exadata, Apache Spark, Tableau, Qlik, Looker, etc. including financial performance, key messaging, and roadmap.Knowledge of AI platforms (AWS, Google, IBM, and Oracle)Certifications:Google Cloud Professional ML Engineer, AWS Certified Machine learning, or IBM certified Data Science professional.
  • Deep domain knowledge in Databases, Analytics, and AI:
  • Database Platforms:MicrosoftAzure SQL Database,Cosmos DB,PostgreSQL, MongoDB,Oracle, MySQL,Redis, Elasticsearch, IBM Db2, Snowflake, Cassandra DB, Maria DB,
  • Analytics Platforms:Fabric, Azure Databricks, Snowflake, real-time analytics, Power BI) OR hands-on experience working with the respective products at the expert level. Hands-on programming experience (Scala, Python, SQL etc.)
  • Understand AI Platforms:Azure OpenAI, Azure AI Services, Azure ML

Responsibilities
  • leveragingprocesses and tools, demos, and programs using consultative salesmethodologyand technicalexpertiseto influence the customer vision;establish
  • Build technical strategy:map the agreed customer vision into a strategy, resolve concerns,preventingandremovingtechnical blockersandvalidatinga strong business case for investment andtranslatedtechnology complexity into business impact.Work with the customer, account team, and partners to orchestrate a roadmap for implementation guiding the customer to choose the best MicrosoftIntelligent Data and Analyticsplatformand win the AI Design,inclusive ofMicrosoft AI, Application services,andDatabases.
  • Design the solution using your technical knowledge, architectural approach, consultancy skills and ourmethodologyto win a customer’s technical decision and meet the customer’s needs; drive POCs/Pilots to create momentum for MVPs, infusing key AI technologies whereappropriateand being technically proficient to do POC with hands-on-skills.
  • identifyingnew opportunities within customerengagement and handing off to the Solution Specialist for pursuit.
  • Be the Trusted advisor and find and understand customers’ pain points and work with partners to design and offer solutions (with business case) to technical leaders by being a Microsoft Intelligent Data and Analytics platform evangelist inclusive of new Data and Analytics projects, modernizing legacy Data Warehouse to the cloud, new Modern Data Warehousing deployments, real-time analytics, and end to end Data, Analytics and AI solutions.
  • the Voice of Customerto share insights and best practices with Engineering, to remove key blockers and drive product improvements.
  • Maintain and grow expertisein Database scenarios including Cosmos DB, SQL DB, PostgreSQLand inAnalytics, Data warehousing, Data Engineering, Data Scienceincluding Intelligent Data and Analytics Platform (Azure SQL DW, Lakehouse architecture, Fabric, Azure Databricks, Power BI), and