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- Cutting-Edge Technology: Work with the latest technologies and methods in Generative AI and data management
- Skills and Expectations: Leadership across feature areas with a focus on quality and attention to detail
What You’ll Do?- Engage in delivering the next-generation Analytics Storage (Unified Analytics Storage) through integrations and query compute capabilities
- Build AI capabilities to analyze next-generation Analytics Storage, develop key metrics, and insights for Retrieval Augmentation Generation (RAG)
- Bachelor's Degree in Computer Science or related technical discipline plus 4+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
Additional or Preferred Qualifications- Bachelor's Degree in Computer Science or related field plus 8+ years of technical engineering experience, OR
- Master's Degree in Computer Science or related field plus 6+ years of technical engineering experience, OR equivalent experience.
- Conflict Resolution, Data Analysis, Decision Making, Design Readiness, Detail Oriented
- Distributed Systems Application Development, Engineering Lifecycle, Livesite Skills
- Negotiation, Oral Communication, Problem Solving, Process and Solution Curiosity
- Product Lifecycle, Programming Language Transferability, Project Management, Project Vision
- Quality Assurance, Readiness Assessments, Resilient System Design, Runtime Analysis
- Software Development, Software Development Methodologies, Strategic Technical Implementation
- Systems Thinking, Technical Domain, Technology Selection, Testing Process, Writes Code, Written Communication
Preferred Skills and Experiences- Data Platforms and Services: Kusto, Azure Delta Lake Storage Gen 2, Azure Kubernetes Service, Azure Event Hubs, Azure Synapse, Azure SQL Data Warehouse, Databricks, Azure Data Factory, Trino, Spark
- Data Structures and Formats: Delta Tables, Delta Log, Common Data Model
- Data Visualization and Analysis: PowerBI, Grafana, Azure Data Explorer
- Data Warehouse Concepts and Design: Data Warehouse, Database architecture design
- Data Quality and Performance: Data Integrity & Quality, High Performance & Scalability
- Data Monitoring and Reporting: Metrics, Telemetry & Monitoring
- Collaborate with stakeholders to gather user requirements and feedback.
- Lead architectural discussions and create design documents.
- Develop and implement testing plans for quality assurance.
- Produce high-quality, maintainable, and efficient code.
- Drive project planning, estimation, and experimentation.
- Maintain and support live services, implementing solutions to complex issues.
- Integrate telemetry for monitoring and refining products.
- Share best practices and enhance software developer tools.
- Maintain communication with partners and stakeholders.
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