Cloud Solution Architecture

We are looking for a highly motivated and passionate **Cloud Solution Architect - Analytics & AI** to drive customer initiatives on the Microsoft Azure Platform in collaboration with customers and the Microsoft field in the **Digital Native accounts segment** of our business. This is a customer facing role, owning overall technical relationship between customer and the Microsoft Azure Data, Advanced Analytics and Artificial Intelligence Platform. You will own the Azure Data Platform & Advanced Analytics technical customer engagements including architectural design sessions, guidance on specific implementation projects and/or MVPs / POCs.

As a Cloud Solutions Architect (CSA) focused on Analytics and AI, you will be the Subject Matter Expert (SME) for helping customers and partners successfully operationalize their Big Data pipeline and ML pipelines and guide them in building innovative solutions that incorporate the very best of Azure Analytics solutions available today.

Your focus will be helping customers build sustainable big data, analytics, and artificial intelligent systems that are easy to manage, maintain and grow.

**Responsibilities**:
**Responsibilities**:

- Understand customers' overall data estate Business and IT priorities and success measures to design data solutions that drive business value.
- Ensure long term technical viability and optimization of production deployments, and lead and advise on migration and modernization using key Azure solutions such as: Azure Synapse Analytics, PowerBI, and other Analytics services.
- Support partner and customer migration efforts targeting Azure Synapse analytics, PowerBI, Azure Data Factory, Azure Data Lake.
- Work with multiple customers and partners to implement POCs/MVPs, guide customers through to production deployment, operationalization, troubleshooting, and optimization of their production deployments resolve blocker escalations, provide technical recommendations and architecture design.
- Ensure customer and partner deployments and solutions exhibit high levels of performance, security, scalability, maintainability, and reliability for new and existing deployments.
- Broadly be willing to work across the entire Azure Data & Al solution space, with key internal stakeholders.
- Identify and build technical collateral or technical assets that help the Microsoft field accelerate Azure consumption.
- Serve as the technical lead and interface among Azure field teams, share best practices and insights to drive product improvement.
- Develop deep relationships with key customer decision makers (both Business and IT) who drive long-term innovation and data platform adoption within their company to enable them to be Azure data advocates.
- Be an Azure Platform evangelist with customers, partners, and external communities.
- Maintain technical skills and knowledge, keeping up to date with market trends and competitive insights; collaborate and share with the technical community while educating customers on Azure platform.

**Qualifications**:**
Qualifications**

Technical Expertise (required):

- 5+ years Data Platform combined experience across one or more of the following areas:

- Big Data and Data Warehouses experience including Azure Synapse Analytics (formerly Azure SQL DW), Snowflake, GCP's Big Query, AWS Redshift.
- Advanced Analytics experience with Azure Synapse.
- Analytics, Azure Databricks, Azure HDInsights, Amazon EMR and data visualization tools (i.e. PowerBl, Tableau).
- Data Engineering expertise in designing and operating DataOps/MLOps pipelines and technologies (Github, Jenkins, Terraform, Kubernetes).
- Data Science and Machine Learning (i.e. TensorFlow, Azure ML, ML Server, or other similar frameworks).
- 5+ years of public cloud expertise designing and maintaining data workloads leveraging laaS and/or PaaS offerings across Azure, AWS or GCP.
- **Breadth Of Technical Experience and Knowledge (preferred)**
- Enterprise-scale technical experience: cloud and hybrid infrastructures, architecture designs, database migrations, and technology management.
- Deep expertise in two or more enterprise data estate products such as: Teradata, Oracle Exadata, IBM Netezza, SAP (HANA, BW), HDInsight, Hadoop, Cloudera/Hortonworks, Apache Spark, Snowflake, MapR, AWS (Redshift, Glue), Google (BigQuery), MemSQL, MarkLogic, Qubole, Pivotal (Greenplum), Actian (Avalanche), Alibaba (MaxCompute).
- Machine Learning including Azure ML, ML Server.
- Artificial Intelligence including BOT framework, Cognitive Services, Cognitive Search.
- Expertise in data estate workloads like HDInsight, Hadoop, Cloudera, Spark, Python.
- Certification in one or more of the following technologies preferred: Cloud, Database, Big Data, BI, Data Science, Machine Learning, Artificial Intelligence.
**Professional Expertise**
- Ability to solve customer's data problems through various cloud technologies (required).
- Proven track record of building deep technical relationships with