Required/Minimum Qualifications
- Relevant certifications from Microsoft or competitive platforms AND 3+ years technical pre-sales or technical consulting experience
- OR Bachelor's Degree in Computer Science, Information Technology, Engineering or related field AND 4+ years technical pre-sales or technical consulting experience
- OR equivalent experience.
- 3+years’ experiencewith cloud and hybrid, or on premises database infrastructures, architecture designs, migrations, industry standards, and/or technology management.
- 2+ years experience creating AI, Database, or Analytics Proof of Concepts (PoC)/Pilots for customers that lead to production deployments.
- Professional level fluency to read, write, and speak English, Spanish and or Brazilian Portuguese.
Additional or Preferred Qualifications
- Experience with Digital Natives, Startups, and ISVs
- Cross organizational and functional collaboration skills to drive the optimal solution for the customer needs
- Demonstratable experience with cloud and hybrid, or on premises database infrastructures, architecture designs, migrations, industry standards, and/or technology management.
- Certification in relevant (Microsoft or industry) technologies or disciplines (e.g., Azure Architect and Development exams, Cloud Platform Technologies, Azure Data & AI, Information Security, Architecture).
- Azure Certifications examples include: Azure Administrator Associate (AZ-104), Designing Microsoft Azure Infrastructure Solutions (AZ-305), 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) with Certifications such as Google Cloud Professional ML Engineer, AWS Certified Machine Learning, or IBM certified Data Science professional.
- Understands Database Platforms such as Microsoft Azure SQL Database, Cosmos DB, PostgreSQL, MongoDB, Oracle, MySQL, Redis, Elasticsearch, IBM Db2, Snowflake, Cassandra DB, Maria DB, etc.
- Understands Analytics Platforms such as 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.)