Required Qualifications (RQs)
- 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
- 2+ years 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 Proofof Concepts (PoC)/Pilots for customersthat lead to production deployments.
Preferred Qualifications (PQs)
- 4+ years technical pre-sales, technical consulting, or technology delivery, or related experience
- 3+ years 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 Proofof Concepts (PoC)/Pilots for customersthat lead to production deployments.
- 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 Competitive Database platforms such as AWS, GCP, Mongo DB, and Oracle. Knowledge of Competitive 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