Required Qualifications (RQs)
- 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.
- UnderstandsAnalytics 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.)
- 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
- 5+ 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 creatingDatabase, Analytics, and AI Proof of Concepts (PoC)/Pilots for customers that 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 Enterprise Data 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.
- Strong Japanese and English communication Skill
- Native Japanese read, write and verbal communication skill.
- Business level English read, write and verbal communication skill.
- Deliver presentation in both English and Japanese skills to non Japanese customers or Events that held in English.
Preferred Qualifications (PQs)
- 5+ years technical pre-sales, technical consulting, or technology delivery, or related experience
- 5+ 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 creatingDatabase, Analytics, and AI Proof of Concepts (PoC)/Pilots for customers that lead to production deployments.