Integration Engineer

Responsibilities : Data Integration Pipeline Development: Design, build, and optimize data integration pipelines using appropriate tools. Ensure data quality, reliability, and scalability. Mentorship and Leadership: Lead and mentor junior data engineers. Share best practices, provide technical guidance, and foster a culture of continuous learning. Data Strategy Contribution: Contribute to the organization’s data strategy by identifying opportunities for data-driven insights and improvements. Participate in smaller focused mission teams to deliver value driven solutions aligned to our global and bold move priority initiatives and beyond. Design, develop and implement robust and scalable data analytics using modern technologies. Collaborate with cross functional teams and practises across the organisation including Commercial, Manufacturing, Medical, DataX, GrowthX and support other X (transformation) Hubs and Practices as appropriate, to understand user needs and translate them into technical solutions. Provide Technical Support to internal users troubleshooting complex issues and ensuring system uptime as soon as possible. Champion continuous improvement initiatives identifying opportunities to optimise performance security and maintainability of existing data and platform architecture and other technology investments. Participate in the continuous delivery pipeline. Adhering to DevOps best practises for version control automation and deployment. Ensuring effective management of the FoundationX backlog. Leverage your knowledge of data engineering principles to integrate with existing data pipelines and explore new possibilities for data utilization. Stay-up to date on the latest trends and technologies in data engineering and cloud platforms. Requirements Qualifications: Required Bachelor's degree in computer science, information technology, or related field (or equivalent experience.) 3 - 5 + years of experience in building/operating data integrations Very strong SQL skills and a proven track record of delivering business value 3 - 5+ years of experience of cloud platforms (AWS, Azure, GCP). A deeper understanding/certification of AWS and Azure is considered a plus Any relevant cloud-based integration certification at foundational level. For example: AWS certified DevOps engineer AWS Certified Developer MuleSoft Certified integration architect Level 1 (Essential), Microsoft Certified Azure Integration and Security. Proficient in RESTful APIs AWS, CDMP, MDM, DBA, SQL, SAP, TOGAF, API, CISSP, VCP (any relevant certification) MuleSoft Understanding of MuleSoft's Anypoint Platform and its components Experience with designing and managing API-led connectivity solutions Knowledge of integration patterns and best practices Proficiency in network architecture and security concepts AWS Experience provisioning, operating, and managing AWS environments Experience developing code in at least one high-level programming language Understanding of modern development and operations processes and methodologies Ability to automate the deployment and configuration of infrastructure using AWS services and tools Experience with continuous integration and continuous delivery (CI/CD) methodologies and tools Microsoft Azure Fundamental understanding of Microsoft Azure and its services Experience with Azure services related to computing, networking, storage, and security Knowledge of general IT security principles and best practices Understanding of cloud integration patterns and Azure integration services such as Logic Apps, Service Bus, and API Management Preferred Subject Matter Expertise: possess a strong understanding of data architecture/ engineering/operations/ reporting within Life Sciences/ Pharma industry across Commercial, Manufacturing and Medical domains. Other complex and highly regulated industry experience will be considered across diverse areas like Commercial, Manufacturing and Medical. Data Analysis and Automation Skills: Proficient in identifying, standardizing, and automating critical reporting metrics and modelling tools Analytical Thinking: Demonstrated ability to lead ad hoc analyses, identify performance gaps, and foster a culture of continuous improvement. Technical Proficiency: Strong coding skills in SQL, R, and/or Python, coupled with expertise in machine learning techniques, statistical analysis, and data visualization. Agile Champion: Adherence to DevOps principles and a proven track record with CI/CD pipelines for continuous delivery.