Technical Sales Specialist – Data and AI (Europe) Full-time

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Responsibilities (Text Only)

– Proactively 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 (e.g., role boundaries, handoff strategies) for extended teams.
– Proactively 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 for MVPs, infusing key AI technologies where appropriate and being technically proficient to do POC with hands-on-skills.
– Proactively enable cross collaboration across teams to drive AI Design Wins and support the customer AI transformation inclusive of AI Applications and data foundation. Support the creation of new pipeline in collaboration with the Specialist and account team by identify new opportunities within customer engagement and hand off to the Solution Specialist for pursuit.
– Be the Trusted advisor and use proactive effort to 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.
– Bethe Voice of Customer to share insights and best practices with Engineering, to remove key blockers and drive product improvements.
– 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.

Qualifications (Text Only)

Required Qualifications (RQs)
– Extensive experience in technical pre-sales or technical consulting
– Demonstratable experience with cloud and hybrid, or on premises database infrastructures, architecture designs, migrations, industry standards, and/or technology management.
– Partners: Experience leveraging partner solutions to solve customer needs and scale opportunities.
– Proof of Concepts: Experience creating Database, Analytics, and AI Proof of Concepts (PoC)/Pilots for customers that lead to production deployments.
– Cross organizational and functional collaboration skills to drive the optimal solution for the customer need

Preferred Qualifications (PQs)
– Certification in relevant technologies or disciplines
– Azure Certifications:Azure Data Engineer Associate (DP 203) or or Azure AI Engineer Associate (AI-102) or Enterprise Data 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

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

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