Senior Lead Data Engineer

Stryker

. Lead the architecture, development, and modernization of scalable enterprise data platforms supporting global procurement analytics and business transformation .

Posted 9/21/2026full-timeRemote • United StatesSenior💰 $118,000 - $255,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and modernizing scalable Azure-based data platforms, with a strong focus on data engineering, analytics, and integration of enterprise data models. Proficient in establishing engineering standards and mentoring teams to enhance data quality and operational efficiency.

Highest-signal resume keywords

Azure Data EngineeringDatabricksSQLPythonETL/ELT Pipeline Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAnalytics EngineeringSoftware EngineeringCloud-Based Data PlatformsData Warehouse ArchitectureData ModelingPerformance OptimizationAPI IntegrationData GovernanceInfrastructure Automation

Soft Skills

MentoringCollaborationInfluencing Technical Direction

Tools & Technologies

Azure Data FactoryAzure DevOpsCI/CD PipelinesDelta LakeSpark

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in Data EngineeringBachelor’s Degree in Data ScienceBachelor’s Degree in Information SystemsBachelor’s Degree in MathematicsBachelor’s Degree in Statistics

Industry Keywords

Enterprise Data PlatformsGlobal Procurement AnalyticsBusiness TransformationTechnical Debt ReductionData QualityProduction Support Practices

Tech Stack

Tools & technologies

AzureCloudERPETLPythonSparkSQL

About the role

Key responsibilities & impact

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 focused on scalability, reliability, automation, technical debt reduction, and maintainability
Design, build, and optimize Azure-based data solutions using Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation
Integrate and harmonize data across multiple ERP systems into common enterprise data models
Partner with analysts, architects, engineers, and business stakeholders to translate business needs into reusable data products and engineering solutions
Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers
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
Support internal data products, APIs, and user-facing applications for procurement insights
Present technical recommendations, roadmap priorities, tradeoffs, and business impacts to stakeholders and leadership

Requirements

What you’ll need

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

Benefits

Comp & perks

Remote work flexibility
10% travel allowance/requirement