Senior Lead Data Engineer (Remote)

PowerToFly; Oregon (WI); Remote; USD 118,000 - 256,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Stock purchase plan

Job summary

Stryker seeks a Senior Lead, Data Engineering to shape enterprise data solutions and mentor engineers. You will drive architecture, build scalable data platforms, and partner with procurement analytics teams to deliver high-impact data products.

Responsibilities include defining multi-year strategy, implementing Azure-based data solutions, integrating ERP data, and presenting recommendations to leadership. A strong focus on governance, reliability, and automation is required.

Qualifications

• Bachelor’s degree in a technical field.
• 6+ years in data engineering or related roles.
• Experience architecting cloud-based data platforms in an enterprise.
• Hands-on Azure data engineering techs: Databricks, Delta Lake, Data Factory, DevOps, CI/CD.
• Strong SQL and Python; Spark experience.
• Experience integrating data from ERP systems and harmonizing data into common models.
• Ability to mentor engineers and influence technical direction.

Responsibilities

• Lead architecture and modernization of enterprise data platforms.
• Define and execute a multi-year data engineering strategy.
• Design and optimize Azure-based data solutions (Databricks, Delta Lake, Data Factory).
• Integrate ERP data into common enterprise data models.
• Partner with analysts, engineers, and stakeholders to translate needs into reusable data products.
• Establish engineering standards and mentor the team.
• Identify AI-enabled approaches to accelerate development and improve data quality.
• Evaluate tools and platform investments for performance and governance.
• Support internal data products, APIs, and analyst-facing apps.
• Present technical recommendations and roadmaps to leadership.

Skills

SQL

Python

Spark

Azure Databricks

Delta Lake

Azure Data Factory

CI/CD pipelines

ETL/ELT pipelines

Data modeling

Architecture leadership

REST APIs

Data governance

Mentoring

Education

Bachelor’s degree in Computer Science, Data Engineering, Data Science, Information Systems, Mathematics, Statistics, or a related technical field.

Master’s degree in Computer Science, Data Engineering, Data Science, Information Systems, Business Analytics, or a related technical field.

Tools

Azure DevOps

GitHub Copilot

ChatGPT

Job description

As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices.

What You Will Do

• 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.

What you need

Required

• 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.

Preferred

• 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.

United States of America Pay Ranges:

• USN: $118,000 - $196,700 USD Annual
• US5: $123,900 - $206,500 USD Annual
• US10: $129,800 - $216,400 USD Annual
• US15: $135,700 - $226,200 USD Annual
• US20: $141,600 - $236,000 USD Annual
• US30: $153,400 - $255,700 USD Annual

View the U.S. work location and transparency guide to find the pay range for your location. Health benefits include: Medical and prescription drug insurance, dental insurance, vision insurance, critical illness insurance, accident insurance, hospital indemnity insurance, personalized healthcare support, wellbeing program and tobacco cessation program. Financial benefits include: Health Savings Account (HSA), Flexible Spending Accounts (FSAs), 401(k) plan, Employee Stock Purchase Plan (ESPP), basic life and AD&D insurance, and short-term disability insurance. Stryker offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 150 million patients annually. Depending on customer requirements employees and new hires in sales and field roles that require access to customer accounts as a function of the job may be required to obtain various vaccinations as an essential function of their role.