Enterprise Data Architect

At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us. With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.

Devoteam Culture & Values: True innovation is born from a powerful culture, fused with meaningful values.

Culture:

• Fair and courageous Everyone is treated fairly – this fuels bravery. At Devoteam, we always make fair decisions. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.
• Ambition and results Ambition is nurtured at every step – this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.
• Learning and innovating Curiosity and learning are at our core – this stimulates innovation. At Devoteam, we are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.
• Caring and sharing A caring attitude is infused into our culture – this encourages sharing. We believe in the power of teams, we promote support and collaboration. At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers.

Values:

• Respect
• Frankness
• Passion

Knowing that success is the result of collaboration. Alone, we go faster, but together, we go further.

To know more about us, please visit:

Summary Introduction:

Enterprise data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles. 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.”

Responsibilities

Facilitate the establishment and execution of the roadmap and vision for information delivery and management, including the enterprise data warehouse, big data, BI & analytics, content management and data management.

Translating business requirements into technical specifications, including data streams, integrations, transformations, databases, and data warehouses.

Work with data engineers to architect and deliver the solutions that fulfill the Business information needs and align with the information vision and strategy.

Apply business strategy while driving technology strategy, balancing short term and long term needs to ensure that the architecture can scale and evolve accordingly.

Engage an end-to-end approach by connecting all the pieces of data to deliver the data while leveraging all available assets.

Provide advice, guidance, direction, and authorization to carry out major plans and procedures to ensure schedule attainment, product development process adherence, and performance and budget targets are met.

Take an active role in the performance management process by completing goal setting, interim review, and year-end review on a timely basis and soliciting ongoing feedback.

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 various data architecture artifacts like conceptual data model, logical data model, physical data model,…