Neuron Health Services - A certified Great Place to Work is dedicated to simplifying healthcare and making it more accessible.
We prioritize seamless experiences, excellence in health insurance management, and innovative technology to better serve our clients and partners.
Rooted in our core valuesGrowth Mindset, Excellence, Resilience, Reliability, and Integritywe provide clarity, protection, and efficiency at every step.
JOB PURPOSE
The Principal ML Platform Engineer is a senior technical leader focused on architecting, developing, and optimizing robust data solutions. This role specializes in the end-to-end movement and transformation of large-scale data across platforms, with deep expertise in designing, implementing, and managing data pipelines that synchronize data warehouses and drive successful cloud integrations. With a strong foundation in AI, machine learning, and advanced analyticsincluding Generative AI, Large Language Models (LLMs), and Agentic AIthis leader translates complex business needs into innovative, scalable data platforms and ensures high-quality, timely data delivery across the organization. Collaboration, technical mentorship, and a passion for advancing data engineering best practices are central to success in this position.
The Principal ML Platform Engineer reports directly to the Chief Strategy and Data Officer and this position is based in our Dubai Silicon Oasis Office.
RESPONSIBILITIES AND DUTIES
- Design, build, and maintain scalable data pipelines to enable seamless movement, transformation, and synchronization of data between diverse sources, data warehouses, and cloud environments.
- Lead the integration and migration of on-premises and cloud data systems, ensuring data is accurate, accessible, and secure throughout the process.
- Implement and optimize solutions for real-time and batch data ingestion, processing, and delivery across multiple cloud platforms.
- Drive best practices for data modeling, ETL/ELT processes, data governance, and automation of data workflows.
- Work closely with data scientists, analysts, and business stakeholders to define and deliver strategic data engineering solutions.
- Champion cloud-native data architectures using platforms such as Google Cloud Platform, Snowflake, and Docker, leveraging modern toolsets to streamline data operations and analytics.
- Ensure data infrastructure is highly available, performant, and cost-efficient while meeting evolving business requirements.
- Mentor and guide engineering teams in adopting agile methodologies and experiment design for rapid, reliable delivery of data-driven projects.
- Monitor and troubleshoot data pipeline performance, proactively identifying areas for improvement and implementing solutions.
- Ensure compliance with data security and governance policies throughout data movement and storage lifecycles.
KNOWLEDGE, SKILLS, AND EXPERIENCE
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related discipline.
- Relevant certifications in cloud data engineering, data platform technologies, or business intelligence preferred.
- 10+ years of hands-on experience in data engineering, with a demonstrated focus on building and managing large-scale data pipelines and cloud data integration.
- Extensive experience with tools and technologies such as Python, SQL, Power BI, Docker, Google Cloud Platform, Snowflake, and Git.
- Proven ability to implement and optimize complex data movement, synchronization, and warehousing solutions across cloud and on-premises environments.
- Deep understanding of ETL/ELT, real-time and batch data processing, and data modeling best practices.
- Expertise in delivering AI/ML-driven analytics projects and business intelligence solutions.
- Strong project management and technical leadership, especially within Agile/Scrum frameworks and model governance environments.
- Exceptional analytical, problem-solving, and communication skills.
- Proven ability to work both independently and collaboratively on high-performing teams.
