Responsibilities

• Working hands-on with prospects and customers to demonstrate value and driving success from demo to proof-of-concept to design and implementation
• Be a trusted advisor to some of our largest customers and guide them in their Azure Synapse Analytics Lifecycle
• Capturing best-practices from engagements, field teams and engineering, and sharing with the worldwide Azure Data Services community via whitepapers, blogs, presentations and training
• Maintaining deep understanding of complementary and competitive technologies and vendors and be able to design and position a more compelling Azure Data Services based solution
• Collaborating with Product Management and Development teams to continuously improve the product
• Organize trainings and workshops to for partner enablement and training
• This role might require ~25% travel.

Qualifications

Technical and consulting experience in the following or related areas:

• Database products, system migrations, project management, customer and partner communications, partner enablement and cloud adoption projects. 
• Demonstrated ability to engage with customers and partners to synthesize a simple solution from ambiguous and/or complex business requirements and constraints
• Understanding of data, application, server and network security
• Hands-on exposure to data engineering development lifecycle, tooling and best practices
• Knowledge with data movement, data transformation, control activities, CI/CD, expression, linked services, dataset, Integration Runtime, data wrangling
• Knowledge of and experience with large-scale database technology (e.g. SQL Server, Netezza, Oracle, Teradata)

HANDS-ON EXPERIENCE AND EXPERTISE IN AT LEAST ONE CATEGORY OF THE BELOW TECHNOLOGIES –

• Azure SQL Data Warehouse, Azure Synapse Dedicated Pool or competing product with understanding of MPP architectures
• Data integration and data management tools (e.g. Informatica, Data Stage, Integration Services, Ab Initio, ODI), Azure Data Factory, Azure Synapse pipelines
• Messaging technologies including AMQP and JMS and enterprise message brokers such as Azure Service Bus, IBM MQ, Apache ActiveMQ, RabbitMQ, Apache Kafka, AWS Kinesis
• Open Source Big Data technologies (e.g. Spark, Hive, Kafka, HBase etc.), knowledge of SQL and KQL (Kusto Query Language)

Excellent written, oral and interpersonal communication skills, particularly the ability to synthesize complex issues/scenarios into easy-to-understand concepts.