Lead Data Architect

2 months ago

London, United Kingdom Munich Re Specialty Group Full time

The Role

Collaborate with business stakeholders, data scientists, analysts, and IT teams end to end to understand business needs and translate them into effective data architecture solutions. Design and implement scalable and efficient data architectures that support business goals, including data warehousing, data lakes, and real-time data processing. Lead the evaluation, selection, and integration of new data technologies and tools to optimise data management processes. Support the development of data products, through robust architecture, data governance policies, ensuring data quality, integrity, security, and compliance with relevant regulations (GDPR). Lead a team to develop and maintain data models, schemas, and data dictionaries to facilitate consistent and accurate data interpretation. Lead the development of data migration strategies to consolidate and centralise data from various sources into a single Platform for MRSG. Drive the adoption of best practices in data architecture, data management, and data lifecycle management. Provide leadership, mentorship, and guidance to the Data Office, Architects and Data Governance. Collaborate with cross-functional teams to develop data-driven insights, dashboards, and reports that support business operations and decision-making. Stay current with industry trends, emerging technologies, and best practices in data architecture, analytics, and insurance industry developments.

General Responsibilities

A pivotal role in the execution of the Data Strategy, within the overall Global Business Strategy A pivotal role in shaping the investment budget for data strategy and digital transformation. Day-to-day operations of the Data Office are carried out professionally and in a manner that supports the business goals of the organisation

Future Data Architecture Responsibilities

Data Architecture is seen as a business role, but one which will require extensive collaboration with IT colleagues across the UK and Globally. In particular relationships with Group Enterprise Architecture are important, with these being collectively responsible for the technical aspects of the MRSG landscape. Such collaboration is assumed in the following:

A high-level target data landscape has been created, consistent with Munich Re’s overall data landscape and supporting business outcomes; help to flesh out the specific details of this in particular areas and contribute to the expansion / revision of the overall target data landscape Develop a consistent, cross entity data model (à logical à physical) Ensure that data is ingested, interfaced, transformed and disseminated in a manner that preserves granularity and lineage, meets the needs of colleagues in the Information, Analytics and Data Governance spaces and is compliant, robust and future proof

Architecture Practice Responsibilities

Work proactively to ensure good data practices are embedded in project design, ensuring that projects are accretive to the overall MRSG data landscape Contribute to the Data Architecture / Governance project control gate, to help projects align to the overall Data Strategy and to incrementally build out the future data landscape Maintain collegiate relationships with counterparts at the Munich Re Group level in order to understand Group direction with respect to data architecture and tooling Collaborate with IT architects (e.g. Solutions Architects) to ensure data and systems work are mutually supportive

What we are looking for

10+ years’ solid hands-on as a lead data architect, with a substantial number of these spent in Insurance and London Market experience a significant advantage Development and maintenance of Future State Data Architectures, aligned with business needs and technological considerations Supporting business and IT projects from a data perspective, ensuring that these help to build towards the overall Future Data Architecture and will not suffer from data problems Gathering data requirements in collaboration with Business Analysts and collation of these to inform the future direction of data capabilities Co-development – with IT colleagues –solution designs that meet business requirements and are accretive to the overall data landscape Creating and maintaining data models of various sorts (conceptual to physical) and, in particular, ones that span organisations consisting of different businesses Work in support of Analytics colleagues (such as Data Scientists), including awareness of areas such as Machine Learning, Natural Language Processing, etc. Conceptual and Logical design of the Data & Analytics Platform; together with experience of data repository consolidation and end user computing Supporting Data Governance colleagues in areas such as metadata management, data lineage, data audits and general data quality improvement Experience of implementing Master Data Management approaches and tooling Selection of external systems / services with a data component – in collaboration with IT Cloud based technologies preferrable MS Azure Strong desire to learn and grow into a wider range of the above disciplines Ability to effectively communicate, present and articulate strategies across various audiences especially with non-technical business functions Willingness to deep dive into specialty insurance business processes Strong drive to get things done in a complex and changing environment Excellent interpersonal skills in areas such as teamwork, facilitation and negotiation Understanding and knowledge of system development life cycle methodologies (such as agile software development, rapid prototyping, incremental, synchronize and stabilize, and DevOps) Ability to estimate the financial impact of technology alternatives in terms of benefit and cost Ability to quickly comprehend the functions and capabilities of existing, new and emerging technologies that enable and drive new business designs and models Bachelor’s degree in a scientific, mathematical, technical or business discipline and/or Relevant professional qualifications (e.g. CDMP Associate or DCAM accreditation etc.) and/or Sustained good performance in a data-centric role over a number of years

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