Technical skills:

• Deep Microsoft Azure product knowledge and understanding of product features, with exposure to other cloud solutions (Google, AWS) a plus.
• Proven track record in designing, developing and implementing data modelling, at a conceptual, logical and physical level.
• Experience with accountability for E2E Data Architecture and Lifecycle (including non-functional requirements and operations) management.
• Understands industry recognised data modelling patterns and standards
• Understands overall IT system design, in particular networking, authorization and authentication protocols, data security, disaster recovery.
• Knowledge of the latest technologies to process large amount of data (Apache Spark; Databricks is a plus)
• Experience in MDM, Metadata Management, Data Quality and Data Lineage tools.
• Expertise in cloud security and identity best practices
• A deep understanding of ETL and ELT tools and techniques
• Strong experience in architecting fit-for-purpose and fit-for-use complex solutions on the Microsoft Azure cloud stack [IaaS, PaaS and SaaS]
• Excellent understanding of architecture patterns and best practices with proven innovative and leading-edge thinking to build cloud-ready systems (e.g., Domain Driven Architecture, multi-tenancy, building for resilience, scalability, performance, and federation, microservices etc.)
• Hands-on work experience on application platforms like .Net, Python, Java etc. preferred
• Understanding of big data platforms concepts and NoSQL technologies, and ability to map such
• The candidate should have experience in modeling data for traditional structured data, as well as information design in Data Lake and NoSQL database engines.
• Fluent with modelling, development and project execution processes around star, snowflake, 3NF, and Data Vault approaches.
• Good experience in working with data using SQLs, Python and Scala in Microsoft based resources like Azure Synapse and Data Lake.
• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Key Accountability:

• Conduct the most complex research using readily available internal and external sources.
• Design and develop complex analytical modeling tools and system.
• Conduct the most complex analysis requiring general understanding of data management and analytics data design principles, concepts, and practices.
• Independently handle complex issues with minimal supervision.

Personal skills:

• A great team player, with the ability to perfectly integrate and play a pivotal role in a team that includes also data scientists, data engineers and data analysts
• Able to appreciate short term vs. long term goals and take both tactical and strategic decisions
• Great communication skills, ability to communicate complex technical concepts to a non-technical audience
• Strong organizational skills, the ideal candidate has the ability to work in a fast-paced environment and has the ability to quickly adapt to changing priorities
• Stays on top of the latest trends and develops expertise in emerging cloud technologies
• Works well as a technical leader and individual contributor.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• Guide the development of an Agile data development experience, when required using DW automation tools.
• Assist the project team in planning and execution to achieve daily and sprint goals.
• Articulate documentation of project artefacts and deliverables.
• Identifies and communicates risks clearly to the Product owner and the team.
• Education of customer on how the technology recommendation/solution planned will fulfil the customer expressed needs