Data & AI Solutions Deployment Architect (United Kingdom)

Bytes is a top provider of premium IT solutions and services, working with SMEs, corporations, and public sector organizations to modernize and digitally transform their IT infrastructures. Founded in 1982, Bytes has experienced significant growth, now employing over 750 people across seven locations in the UK and Ireland, with a turnover surpassing £1.8 billion in 2023.

At Bytes, we nurture talented individuals to achieve remarkable outcomes and are dedicated to supporting our employees through continuous training, guidance, and development to help you advance and fulfil your career goals. We foster a culture of innovation, collaboration, recognition and inclusivity and offer a wide range of benefits to support staff wellbeing.

PURPOSE OF JOB:

The Data & AI Solutions Deployment Architect will be instrumental in architecting and deploying Azure Data & AI Solutions. A solid, technical, ‘hands-on’ ( not just the theory ) grasp of Azure Fabric is essential as we navigate clients through all of the infrastructure, coding, and product development lifecycle challenges around successful Data and AI implementation and deployment.

This customer-centric position involves delivering projects, conducting workshops and physically working on client’s environments via Python, and C#. This role would suit an experienced Data platform engineer or Data Solutions Architect who thrives in working across multiple projects with a diverse range of clients, and who places the importance of bridging the gap between complex data problems and real life product requirements to non-technical stakeholders.

KEY RESPONSIBILITIES:

• Have 5+ years of technical consulting or a similar chronology of demonstrable success in coding and deploying Data and AI models onto Azure environments.
• At least one year using Azure Fabric
• Create scalable and reliable data pipelines for data processing, transformation, and storage.
• Establish and enforce data governance policies and be ‘hands-on’ in exploratory data analysis to identify and measure quality gaps that are a block to Data and Ai implementation.
• Implement robust security measures to protect sensitive data within Azure environments.
• Integrate AI and machine learning models into data pipelines and applications.
• Develop and deploy AI solutions using Azure Machine Learning services.
• Have a knowledge of top ML libraries scalable across multiple CPU’s and GPU’s. Such as TensorFlow, PyTorch, Keras, OpenAI, XGBoost. And have used these in a commercial setting.
• Troubleshoot and resolve issues related to data processing and AI model performance.
• Collaborate with cross-functional teams to understand data requirements.
• Be able to troubleshoot clients Data and Ai code scripts and make quality, performance, and efficiency recommendations.

INDIVIDUAL RESPONSIBILITIES:

• Ability to independently analyse and solve complex data and AI engineering challenges.
• Stay updated on the latest Azure data and AI technologies and best practices.
• Proactively identify opportunities to enhance skills and knowledge.
• Effectively communicate technical concepts to both technical and non-technical stakeholders.
• Collaborate with team members to share insights and contribute to a knowledge-sharing culture.

QUALIFICATIONS, EXPERIENCE, & SKILLS:

Professional Qualifications

• Relevant Azure certifications such as Microsoft Certified: Azure Data Engineer Associate or similar - DESIRABLE

Years of Experience

• 5+ years working with production data workloads in Azure - ESSENTIAL

Other Requirements

• Proficiency in Azure data services (Azure Data Factory, Azure Databricks, Azure Synapse Analytics, etc.) - ESSENTIAL
• Experience with AI development using Azure Machine Learning - ESSENTIAL
• Strong programming skills in languages such as Python, SQL, or C# - ESSENTIAL

CORE COMEPTENCIES & SKILLS:

• Expertise in designing and implementing data models and data warehousing solutions.
• Knowledge of machine learning algorithms and experience in deploying models in production.
• In-depth understanding of Azure services and capabilities related to data and AI.
• Ability to analyse complex problems and develop innovative, scalable solutions.
• Proven ability to work effectively in a collaborative, cross-functional team environment.