Sr Technical Architect Data System(NCS/Job/ 1483)

Senior Technical Architect – Data Systems

We are adding to our diverse team of experts and are looking to hire those who are committed to building a culture that enables the creation of innovative solutions for our business and clients. 

The Company

We offer the financial strength and stability that comes with being part of the world's preeminent insurance and reinsurance brand. Our risk experts work together to assemble the right mix of products and services to help our clients stay competitive – from traditional reinsurance coverages, to niche and specialty reinsurance as well as excess and supplemental insurance products.

The Opportunity

The Senior Technical Architect (Data Systems) is in charge of architecting and overseeing the establishment of the Digital Data Landscape within MRSI.

You will oversee the development of new data engineering and analytics capabilities.

You will also oversee strategic data priorities of the various lines of business within MRSI and collaborate with business leaders and Operations stakeholders to determine the most scalable architecture that can be realized at the lowest risk.

You will guide Data and Analytics initiatives on data acquisition, storage, operation and analysis patterns that optimize the cost of delivering data engineering capabilities to MRSI business.

You will drive the vision for data activities and champions for data ownership, standardization, accessibility, and governance as follows. The primary outcome sought from the Senior Technical Architect (Data Systems) is the establishment and operation of an environment that makes data and information accessible to all departments and personnel across the business.

Your role will also manage the lifecycle of data and information in order to comply with the business’s requirements.

In his/her leadership position, the Senior Technical Architect (Data Systems) also mentors key personnel within the department, assisting in the execution of their function upon request, and encouraging the constant growth in their professional skills. The right candidate will have strong leadership and negotiation skills while being future focused.

Responsibilities

• Drive the architecture and design of the Digital Data Landscape and maintaining the overall transformation roadmap for Data & Informatics
• Own the lifecycle of topologies deployed to support solutions including but not limited to continual capacity analysis and optimization w.r.t. configuration, uptime and consumption levels.
• Closely follow new technologies and methodologies regarding Azure / Cloud native data engineering practices, research ways to integrate new ideas to leverage emerging data engineering capabilities / patterns.
• Work with business solutions teams to identify requirements for digital data landscape
• Construct concept, identify technical solutions and options, design high level and low level architecture for Data & Informatics solutions
• Collaborate and socialize ideas in order to get buy in for technical solutions
• Architect, design, deploy and operate solutions using IaaS, PaaS and SaaS resources on Azure using cost optimized patterns and industry best practices.
• Develop code patterns for selected solutions
• Swarm on stories or bugs as needed.

Qualifications:

• 10+ years of hands-on experience designing and implementing large scale multi-tenant distributed data architectures for business intelligent and/or OLTP systems
• A minimum of seven years of hands-on experience architecting, designing and implementing multi-tenant solutions for data governance, data pipelines for near real-time data warehousing, and machine learning solutions
• Five or more years of hands-on experience designing and developing multi-tenant solutions using Power BI, Power BI Embedded, Power BI Services, Power BI Gateway, and Power BI Dataflow
• 10+ years of hands-on experience designing and implementing large scale multi-tenant data pipeline (TB / PB size) including Change Data Capture (CDC) solutions for structured, semi-structured, and unstructured data in batch and real-time environments