Stryker—Senior Technical Lead, Data Architecture & Design

Job description

Description: Work Flexibility: Hybrid Senior Technical Lead: We are looking for an experienced Senior Technical Lead to lead the end-to-end delivery of scalable, secure, and high-performing enterprise data built on Azure and Databricks. The role will work closely with Enterprise Architecture, Platform & Engineering, Business Analysts, Implementation Partners, Product Owners, and Service Delivery Teams to ensure successful delivery from solution design through production deployment and transition to service delivery. What you will do: - Engage with delivery partners in technical discussions, solution reviews, and design evaluations. - Provide technical guidance and oversight throughout the delivery lifecycle to delivery partners. - Ensure solutions adhere to approved architecture, engineering standards, governance requirements, and best practices. - Lead the implementation of ETL/ELT pipelines, data lakes/lakehouses, data warehouses, BI integrations, and reusable data products. - Drive alignment on standards across security, privacy and compliance requirements with implementation partners. - Optimize performance, scalability, reliability, and cloud cost efficiency across data platforms and solutions. - Own end-to-end technical delivery including solution design, development, testing, deployment, hypercare, and transition to operations. - Guide teams in following approved CI/CD and version control standards, with a strong emphasis on automated, consistent, and reliable deployments through Azure DevOps. - Review data solutions, technical assessments, change-impact analysis, and risk identification and mitigation. - Collaborate with Enterprise Architecture, Platform, PMO, Business Analysts, Product teams and other internal cross-functional stakeholders. - Mentor data engineers and analysts and promote engineering standards, design best practices, and continuous improvement. What you need: - Bachelor's degree in Computer Science, Data Analytics, or a related field. Degree in Statistics, and Data Science is an added advantage. - 10-12 years of related data engineering and architecture experience. - Strong experience in enterprise data engineering and data architecture. - Hands-on expertise with Azure Databricks, Azure Data Factory/Synapse, ADLS, SQL, Spark/PySpark, and Delta Lake. - Strong understanding of data modeling, ETL/ELT architecture, data governance, security, and access-control concepts. - Experience designing scalable cloud data platforms and optimizing performance and cost. - Experience with CI/CD and Azure DevOps for automated code promotion and deployment. - Strong understanding of testing, release management, production deployment, and operational support practices. Travel Percentage: None