Job
Description
We are looking for a Senior Data Lead to lead enterprise-level data modernization and innovation. In this highly strategic role, you will design scalable, secure, and future-ready data architectures, modernize legacy systems, and provide trusted technical leadership across both technology and business teams. This is a unique opportunity to make a company-wide impact by influencing data strategy and enabling smarter, faster decision-making through data. Key Responsibilities Architect & Design: Lead the development of robust, scalable data models, data management systems, and integration frameworks to ensure enterprise-wide data accuracy, consistency, and security. Domain Expertise: Act as a subject matter expert across key business functions such as Supply Chain, Product Engineering, Sales & Marketing, Manufacturing, Finance, and Legal. Modernization Leadership: Drive the transformation of legacy systems and manage end-to-end cloud migrations with minimal business disruption. Collaboration: Partner with data engineers, scientists, analysts, and IT leaders to build high-performance, scalable data pipelines and transformation solutions. Governance & Compliance: Establish and maintain data governance frameworks including metadata repositories, data dictionaries, and data lineage documentation. Strategic Advisory: Provide guidance on data architecture best practices, technology selection, and roadmap alignment to senior leadership and cross-functional teams. Mentorship: Serve as a mentor and thought leader to junior data professionals, fostering a culture of innovation, knowledge sharing, and technical excellence. Innovation & Trends: Stay abreast of emerging technologies in cloud, data platforms, and AI/ML to identify and implement innovative solutions. Communication: Translate complex technical concepts into clear, actionable insights for technical and non-technical audiences alike. Required Qualifications 10+ years of experience in data architecture, engineering, or enterprise data management roles. Demonstrated success leading large-scale data initiatives in life sciences or other highly regulated industries. Deep expertise in modern data architecture paradigms such as Data Lakehouse, Data Mesh, or Data Fabric. Strong hands-on experience with cloud platforms like AWS, Azure, or Google Cloud Platform (GCP). Proficiency in data modeling, ETL/ELT frameworks, and enterprise integration patterns. Deep understanding of data governance, metadata management, master data management (MDM), and data quality practices. Experience with tools and platforms including but not limited to: Data Integration: Informatica, Talend Data Governance: Collibra Modeling/Transformation: dbt Cloud Platforms: Snowflake, Databricks Excellent problem-solving skills with the ability to translate business requirements into scalable data solutions. Exceptional communication skills and experience engaging with both executive stakeholders and engineering teams. Preferred Qualifications (Nice to Have) Experience with AI/ML data pipelines or real-time streaming architectures. Certifications in cloud technologies (e.g., AWS Certified Solutions Architect, Azure Data Engineer). Familiarity with regulatory frameworks such as GxP, HIPAA, or GDPR. Show more Show less
