Remote Senior Data Platform Lead (Azure & AI)

Stryker

Kalamazoo (MI)

Remote

USD 118,000 - 256,000

Full time

14 days+

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Benefits offered by this job

Health insurance

401(k) plan

Employee Stock Purchase Plan (ESPP)

Wellbeing program

Paid holidays

Job summary

Stryker is seeking a Senior Lead Data Engineer to serve as a technical leader for enterprise data solutions, guiding Azure-based data initiatives and procurement analytics while mentoring engineers and strengthening engineering practices.

You'll shape scalable data platforms, drive multi-year strategy, and partner with analysts, architects, and business stakeholders to translate complex needs into reusable data products and robust pipelines that enhance decision-making across the enterprise.

Qualifications

Bachelor’s degree in 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 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 translate complex business requirements into scalable, maintainable engineering solutions.

Responsibilities

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 DevOps, 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.