Note: The job is a remote job and is open to candidates in USA. Stryker is seeking a Senior Lead Data Engineer to help shape enterprise data solutions. The role leads complex data initiatives, develops scalable Azure-based data platforms for procurement analytics, establishes engineering standards, and mentors engineers while partnering with technical and business stakeholders.
Responsibilities
- Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation
- Define and help execute a multi-year data engineering strategy focused on platform 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, Azure DevOps, 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 translate complex business needs into reusable, scalable data products and engineering solutions
- Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team
- Identify and implement AI-enabled approaches that 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 the development of internal data products, APIs, and user-facing applications that simplify access to procurement insights and improve analyst productivity
- Present technical recommendations, roadmap priorities, tradeoffs, and business impacts to technical and non-technical stakeholders, including leadership teams
Skills
- 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 DevOps, 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 data from multiple ERP or enterprise source systems and harmonizing inconsistent master, supplier, purchasing, or transactional data into common data models
- 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 translate complex business requirements into scalable, maintainable engineering solutions
- Master's degree in Computer Science, Data Engineering, Data Science, Information Systems, Business Analytics, or a related technical field
- Experience supporting procurement, supply chain, manufacturing, finance, or ERP analytics in a global enterprise environment
- Experience building or modernizing enterprise data platforms, Lakehouse architectures, or cloud analytics ecosystems at scale
- Hands-on experience with multiple ERP platforms, such as SAP ECC, SAP S/4HANA, Oracle, JD Edwards, Infor, QAD, or Microsoft Dynamics
- Full-stack engineering experience, including React, Next.js, Vercel, API development, authentication, and internal web application development
- Experience using AI-assisted engineering tools and workflows, such as GitHub Copilot, ChatGPT, Claude, Cursor, AI coding agents, AI-assisted testing, or AI-assisted documentation
- Experience designing internal tools, data products, APIs, or analyst-facing applications that improve productivity and simplify access to insights
- Experience leading cloud modernization, platform migration, technical debt reduction, automation, or data quality improvement initiatives
- Experience with Power BI, Tableau, or similar business intelligence and visualization tools
- Demonstrated curiosity and continuous learning mindset, with a track record of experimenting with emerging technologies and applying them to practical engineering or analytics use cases
Benefits
- Work Flexibility: Remote
Company Overview
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