Senior Data Architect

Cognizant is a world leader in delivering digital transformation solutions to Life Sciences. Through our knowledge and expertise in Automation, MES & Digital, we deliver stable manufacturing systems that are optimized to improve operational efficiencies, whilst maintaining compliance. Our specialist engineering teams have the aptitude to deliver and support Pharma 4.0 architectures and solutions covering all IT, OT and IoT applications, infrastructures and services. Operating across 5 continents and with over 300.000 skilled employees, Cognizant partners with the leading Life Sciences companies globally to provide performance improvements, reduced costs and improve time to market. We are your single end to end partner for consultancy, design implementation, optimization and support for all applications in the Pharmaceutical and Biotechnology Manufacturing stack. We're looking for dedicated, innovative and driven talent to join our expanding team. Location: Dublin, Ireland (Hybrid) Role: The Senior Data Platform & Architecture Lead is responsible for defining, governing, and advancing the data platform architecture that enables trusted, scalable, secure, and reusable data capabilities across the enterprise. This role provides technical leadership for data platform strategy, architecture standards, and engineering delivery, ensuring solutions are aligned with business priorities, compliance requirements, and enterprise technology direction. The role partners closely with data engineering, analytics, governance, security, application teams, product owners, and business stakeholders to design data solutions that improve availability, quality, interoperability, and time-to-insight. It requires strong ownership of architectural decisions, the ability to influence cross-functional teams, and the judgment to balance innovation with operational stability and regulatory expectations. This is a senior leadership role for someone who can combine hands-on architecture thinking with strategic leadership, vendor coordination, and practical delivery oversight. Job Description: Design and deliver enterprise data warehouse solutions within a life science industry. Analyse source data, data flows, and business requirements Work closely with business stakeholders, engineers, testers, and architects Produce HLDs, Architecture Design Decisions, and governance documentation Embed data governance, lineage, auditability, and regulatory controls into solution design What you need: 8+ years in data engineering, data architecture, enterprise architecture, or platform engineering. Strong hands-on Data Lake Architecture, Data Warehousing design experience. Strong Data Modeling and integration and DataBricks. Experience leading complex data initiatives across multiple teams or domains. Hands on experience in: Data Lake Architecture - Storage, compute separation, reusable platform design Data Warehousing - Dimensional and analytical modeling, performance, Data Modeling - Domain-driven models, canonical structures, standards Data Integration - ETL/ELT, APIs, events, file-based patterns, orchestration Security and compliance - Privacy, access control, auditability CI/CD - Promotion, version control, testing, deployment automation API Architecture - Particularly where data domains expose reusable services Metadata management - Technical and business metadata, discoverability, lineage DataBricks - Data engineering patterns, scaling, orchestration SQL - Essential for design review and platform understanding Industrial Data Platforms Data Product Architecture, IIoT Data Integration, Streaming & Event Driven Architecture (Kafka, Event Hubs, MQTT, etc.) Working knowledge of the following is required: Java, Python, Spark, MLOps platforms, Model Serving and Deployment, Data and Quality Governance. Experience in global or enterprise-scale environments is highly valuable. Life Science industry experience preferred.