Cloud Data Architect

Job Description

The Tech Collective is a fast-growing consultancy powered by Implement. We help organisations unlock the immense potential of data, AI and analytics to ensure they are fit for the digital future. Through co-creation and passionate advisory, we aim to make data easy to handle and provide useful insights. In our collective, you will find people with a delicious combination of nerdiness and infectious energy. We are passionate about technology, but we also have a genuine interest in people.

We are looking for a highly skilled and experienced cloud data architect to join our team. The ideal candidate will have a deep understanding of the modern data stack, cloud architecture (preferably with a focus on Microsoft Azure, but AWS or GCP is also ok), integration architecture and data modelling. This role is vital to ensuring the seamless integration, management and deployment of data and analytics solutions that support our clients’ business needs.

Your key responsibilities will be

• Design and implement modern data architectures: lead the design and implementation of scalable, robust and secure data systems using modern data stack technologies. Ensure architecture is aligned with business objectives and best practices.
• Support data platform teams: work with data platform teams to design and implement operating models that support efficient data processing, integrations, reporting and AI model deployment and execution.
• Cloud architecture expertise: develop and manage cloud-based data solutions on platforms such as Microsoft Azure, GCP or AWS. Optimise cloud infrastructure for performance, cost and scalability.
• Integration architecture: design and implement integration solutions that connect disparate business systems and data sources to ensure seamless data flow across the organisation.
• Data modelling: design and develop data models that support business processes, analytics and reporting requirements. Ensure that data models are optimised for performance and scalability.
• Deploy analytics and AI solutions: lead the deployment of analytics and AI solutions to ensure they are integrated into existing systems and processes. Provide guidance on best practices for model deployment and monitoring.
• Stakeholder collaboration: work closely with cross-functional teams, including business stakeholders, data scientists and IT, to understand data requirements and deliver solutions that meet business needs.
• Mentorship and leadership: provide mentorship and guidance to junior data engineers and other team members. Foster a culture of continuous learning and improvement within the team.
• Stay current with emerging technologies: continuously evaluate and recommend new tools and technologies that can improve the efficiency and effectiveness of data engineering processes for our clients.

Our key requirements are

• Educational background: bachelor’s degree in Computer Science, Engineering, Information Technology or a related field (master’s degree preferred).
• Experience: at least 5 years of experience in data engineering, with a strong focus on cloud architecture, data integration and data modelling.
• Technical expertise:
  • Deep understanding of the modern data stack and its components.
  • Proven experience with cloud platforms such as Microsoft Azure, GCP or AWS.
  • Strong skills in data modelling, ETL processes and data integration, having been part of one or several data platform teams.
  • Experience in deploying analytics and AI solutions in a cloud environment.
    
• Analytical skills: exceptional problem-solving skills with the ability to design innovative solutions to complex data challenges.
• Communication skills: excellent communication and interpersonal skills, with the ability to convey technical concepts to non-technical stakeholders.
• Leadership ability: proven ability to lead projects and mentor junior team members.
• Certifications: relevant certifications in cloud technologies are a plus, such as:
  • Microsoft Certified: Azure Solutions Architect Expert
  • Microsoft Certified: Data Engineering certifications
  • Snowflake certifications
  • Databricks certifications
  • Kafka certifications

Apply now

The application deadline is 15 December 2024, but we will conduct interviews on an ongoing basis, so please apply as soon as possible.

For further information please reach out to [email protected].

We look forward to hearing from you!