As a Senior Data Engineer, you will play a crucial role in designing, building, and maintaining our data infrastructure. Your expertise in Databricks, PySpark, SQL, and other related technologies will be instrumental in driving data-driven decision-making across the organization. You will play a pivotal role in building, maintaining, and enhancing our systems across the organization. This is a fantastic global opportunity to use your proven agile delivery skills across a diverse range of initiatives, utilize your development skills, and contribute to the continuous improvement/delivery of critical IT solutions.
Key Responsibilities:
• Data Pipeline Development: Design, build, and optimize data pipelines using Databricks and PySpark. Ensure data quality, reliability, and scalability.
• Application Transition: Support the migration of internal applications to Databricks (or equivalent) based solutions. Collaborate with application teams to ensure a seamless transition.
• 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 practices across the organization, 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 optimize performance, security, and maintainability of existing data and platform architecture and other technology investments.
• Participate in the continuous delivery pipeline. Adhere to DevOps best practices for version control, automation, and deployment. Ensure 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:
• Minimum 5 years of experience in data engineering with a strong understanding of PySpark and SQL, building data pipelines, and optimization.
• Minimum 5 years of experience in data engineering and integration tools (e.g., Databricks, Change Data Capture).
• Minimum 5 years of experience utilizing cloud platforms (AWS, Azure, GCP). A deeper understanding/certification of AWS and Azure is considered a plus.
• Experience with relational and non-relational databases.
• Any relevant cloud-based integration certification at a professional level.
• Proficient in RESTful APIs.
• AWS, CDMP, MDM, DBA, SQL, SAP, TOGAF, API, CISSP, VCP (any relevant certification).
• 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 experience: 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 Qualifications:
• 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 modeling 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.
• Cross-Cultural Experience: Work experience across multiple cultures and regions, facilitating effective collaboration in diverse environments.
• Innovation and Creativity: Ability to think innovatively and propose creative solutions to complex technical challenges.
• Global Perspective: Demonstrated understanding of global pharmaceutical or healthcare technical delivery, providing exceptional customer service and enabling strategic insights and decision-making.
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