Data & AI Solutions Engineer

Job Responsibilities

• Lead the end-to-end lifecycle of data and AI projects.
• Design, develop, and maintain AI-enabled solutions, ensuring successful transition from prototypes to scalable production systems.
• Enable AI-powered self-service analytics and drive organization-wide AI adoption.
• Collaborate with business stakeholders to identify AI, BI, and ML opportunities and translate requirements into scalable solutions.
• Coordinate with internal teams and external partners to ensure timely delivery aligned with quality standards and milestones.
• Maintain a centralized data architecture (Lakehouse) and ensure a single source of truth across all analytics platforms.
• Design user-friendly dashboards and interfaces to improve usability and business adoption of AI solutions.
• Develop and optimize data pipelines and machine learning workflows for scalability, reliability, and performance.
• Ensure compliance with data governance policies, including data privacy, access control, and data cataloging.
• Stay updated with emerging trends in AI, ML, data engineering, and BI, and recommend improvements.
• Conduct training and awareness sessions to promote data literacy and AI adoption across teams.

Person Specifications

• Bachelor’s degree in Data Science, Artificial Intelligence, or a related field.
• Minimum 2 years of hands-on experience in AI/ML implementation, data engineering, or similar roles.
• Relevant certifications (e.g., Azure AI Engineer, Azure Data Engineer, or equivalent).
• Experience working with cloud platforms and data services.
• Hands-on experience with tools such as Databricks, Microsoft Fabric, or similar platforms.
• Strong proficiency in SQL and Python.
• Solid understanding of machine learning concepts and practical implementation.
• Good knowledge of data governance, privacy, and security frameworks.
• Strong teamwork, communication, and project management skills.
• Excellent analytical thinking, problem-solving, decision-making, and time management skills.
• Ability to work independently with minimal supervision and under flexible or extended working hours when required.