Senior Lead Data Engineer

Stryker seeks a Senior Lead Data Engineer to serve as a technical leader for enterprise data solutions. The role will guide complex data initiatives spanning data platform architecture, Azure-based engineering, and procurement analytics, while mentoring engineers and strengthening engineering practices.

This position focuses on shaping and delivering scalable enterprise data platforms that enable global procurement analytics and support business transformation. The Senior Lead Data Engineer will drive a multi-year engineering strategy, improve platform maintainability and reliability, and translate complex business needs into reusable data products and engineering solutions.

• Lead the architecture, development, and modernization of scalable enterprise data platforms supporting global procurement analytics and business transformation.
• Define and help execute a multi-year data engineering strategy covering scalability, reliability, automation, technical debt reduction, and long-term maintainability.
• Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, and Azure Dev Ops, including CI/CD pipelines and infrastructure automation.
• Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models.
• Partner with procurement analysts, architects, engineers, and business stakeholders to convert complex business requirements into scalable, reusable data products.
• Set engineering standards, perform architecture reviews, improve documentation, and mentor engineers to raise the team’s technical capability.
• Identify and implement AI-enabled approaches to accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity.
• Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational efficiency.
• Support internal data products, APIs, and user-facing applications that simplify access to procurement insights.
• Present technical recommendations, roadmap priorities, tradeoffs, and business impacts to technical and non-technical stakeholders, including leadership teams.

• Bachelor’s degree in Computer Science, Data Engineering, Data Science, Information Systems, Mathematics, Statistics, or a related technical field.
• 6+ years of experience in data engineering, analytics engineering, software engineering, or enterprise data platform development.
• Proven experience architecting, building, and modernizing scalable cloud-based data platforms in an enterprise environment.
• Hands‑on experience with Azure-based data engineering technologies including Databricks, Delta Lake, Azure Data Factory, Azure Dev Ops, CI/CD pipelines, and infrastructure automation.
• Strong proficiency in SQL and Python, with experience using Spark or similar distributed data processing frameworks.
• Experience designing reliable ETL/ELT pipelines, data warehouse or Lakehouse architectures, data models, and performance‑optimized analytics solutions.
• Experience integrating and harmonizing data from multiple ERP or enterprise source systems into common data models, including master, supplier, purchasing, and transactional data.
• Experience with API integrations, REST services, authentication, security, data governance, and production support practices.
• Demonstrated ability to establish engineering standards, conduct architecture reviews, improve documentation, mentor engineers, and influence technical direction without direct authority.
• Ability to partner with analysts, engineers, architects, and business stakeholders to…