Data Architect Senior Manager at AXA

Makati, Metro Manila, Philippines -

Full Time

Start Date

Immediate

Expiry Date

04 Aug, 26

Salary

0.0

Posted On

06 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, Data Modeling, Azure Data Lake Storage, Azure Data Factory, Azure Analysis Services, Azure Databricks, NoSQL Databases, Predictive Analytics, Data Visualization, System Development Life Cycle, Project Management, DAMA-DMBOK, Database Optimization, Stakeholder Management, Technical Specification Writing, Enterprise Data Management

Industry

Insurance

Description

Data Architect: Can translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. The data architect is responsible for visualizing and designing an organization’s enterprise data management framework. This framework describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data. The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge (DAMA-DMBOK). Objectives of this role Designing, creating, deploying, and managing AXA’s data architecture. Make sure that data is accessible, secure, and reliable by developing and maintaining data frameworks, models, and policies. Understand the overall data requirements and improve databases to work faster and handle more data efficiently. Stay up to date with developments in the data analytics industry Responsibilities Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses Defining the data architecture framework, standards, and principles, including modeling, metadata, security, reference data such as product codes and client categories, and master data such as clients, vendors, materials, and employees Defining reference architecture, which is a pattern others can follow to create and improve data systems Defining data flows, i.e., which parts of the organization generate data, which require data to function, how data flows are managed, and how data changes in transition Collaborating and coordinating with multiple departments, stakeholders, partners, and external vendors Skills and Qualifications Must understand the system development life cycle, project management approaches, and requirements, design, and test techniques. Understands established data management and reporting technologies, and have some knowledge of columnar and NoSQL databases, predictive analytics, data visualization, and unstructured data. Solid understanding of the cloud, databases, and the applications and programs used by those databases. Familiarity with the Azure ecosystem, specifically Azure Data Lake Storage (ADL), Azure Data Factory (ADF), Azure Analysis Services (AAS) and Azure Databricks Understand data modeling and design, including conceptualization and database optimization, and demonstrate a commitment to continuing education. People skills. Must be articulate, persuasive, and good salespeople, must conceive and portray the big data picture to stakeholders. Preferred qualifications With a minimum of 8 years proven work experience as a data architect/engineer or similar role Excellent communication and collaboration skills Innovative mind with a passion for continuous learning Familiarity with the DAMA-DMBOK framework General knowledge of building a data warehouse Bachelor’s degree (or equivalent) in computer science, mathematics, or related field

Responsibilities

The role involves designing and managing the organization's enterprise data architecture framework to ensure data is secure, reliable, and accessible. Key duties include translating business requirements into technical specifications and defining data standards, flows, and reference architectures.