Microsoft Senior Technical Specialist - Data AI 

Singapore 

837881757

Mandatory Requirements:

5+ years technical pre-sales or technical consulting experience

• OR Bachelors Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience
• OR Masters Degree in Computer Science, Information Technology, or related field AND 3+ years technical pre-sales or technical consulting experience
• OR equivalent experience
• OR experience working with customers, account teams, and partners building relationships and driving technical solutions that deliver desired business outcomes

Other Requirements:

• 6+ years technical pre-sales, technical consulting, or technology delivery, or related experience
  • Partners: Experience leveraging partner solutions to solve customer needs and scale opportunities.
  • Proof of Concepts: Experience creating Database, Analytics, and AI Proofof Concepts(PoC)/Pilots for customers​that lead to production deployments.
  • Cross organizational and functional collaboration skills to drive the optimal solution for the customer needs
• 4+ years experience with cloud and hybrid, or on premises infrastructures, architecture designs, migrations, industry standards, and/or technology management.
• 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) or or Azure AI Engineer Associate (AI-102) or EnterpriseData Analyst Associate (DP 600) or Azure Cosmos DB Developer Specialty (DP 420) or Fabric Analytics Engineering Associate (DP- 600).
  • Knowledge of Database platforms such as AWS, GCP, Mongo DB, and Oracle. Knowledge of Intelligent 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:
• Understands Database Platforms: Microsoft Azure SQL Database, Cosmos DB, PostgreSQL, MongoDB, Oracle, MySQL, Redis, Elasticsearch, IBM Db2, Snowflake, Cassandra DB, Maria DB, etc.
• Understands Analytics Platforms: Fabric, Azure Databricks, Snowflake, real-time analytics, Power BI) OR hands-on experience working with the respective products at the expert level. 3+ years of hands-on programming experience (Scala, Python, SQL etc.)
• Understand AI Platforms: Azure OpenAI, Azure AI Services, Azure ML

• Own technical discussions with customers leveraging processes and tools, demos, and programs using consultative sales methodology and technical expertise to influence the customer vision; establish rules of engagement for extended teams.
• Build technical strategy: map the agreed customer vision into a strategy, resolve concerns, preventing and removing technical blockers and validating a strong business case for investment and translated technology 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 Microsoft Intelligent Data and Analytics platform and win the AI Design, inclusive of Microsoft AI, Application services, and Databases.
• Design the solution using your technical knowledge, architectural approach, consultancy skills and our methodology to win a customer’s technical decision and meet the customer’s needs; drive POCs/Pilots to create momentum infusing key AI technologies where appropriate
• Support the creation of new pipeline in collaboration with the Specialist and account team by identifying new opportunities within customer engagement
• Maintain and grow expertise in Database scenarios including Cosmos DB, SQL DB, PostgreSQL and in Analytics, Data warehousing, Data Engineering, Data Science including Intelligent Data and Analytics Platform (Azure SQL DW, Lakehouse architecture, Fabric, Azure Databricks, Power BI), and relevant AI technologies while keeping up to date with market trends and competitive insights; collaborate and share with the Data & AI technical community.
• Be the Trusted advisorand use proactive effort to find and understand customers’ pain points and work with partners to design and offer solutions to technical leaders by being a Microsoft AI and Analytics platform evangelist.
• Bethe Voice of Customerto share insights and best practices with Engineering, to remove key blockers and drive product improvements.