Manager Data Engineering

Data Engineering Manager

Fueled by innovation at the intersection of biology and technology, we're developing the next generation of smarter, less invasive, more personalized treatments.

Are you passionate about improving and expanding the possibilities of Orthopaedics? Ready to join a team that's reimagining how we heal? Our Orthopaedics teams help keep more than 6 million people moving each year while delivering clinical and economic value to surgeons and healthcare systems. Our teams build solutions for joint reconstruction; trauma and craniomaxillofacial; sports, extremities, and elective foot and ankle; spine; and robotics and digital surgery.

Your unique talents will help patients on their journey to wellness.

Purpose:

Orthopedics Supply Chain is recruiting for a Data Engineering Manager located in Warsaw, IN, Raynham, MA, Raritan, NJ, West Chester, PA, Palm Beach Gardens, FL. Remote work may also be considered in certain situations.

What's in it for you?

As a Data Engineering Manager, you will play a pivotal role in shaping the data engineering strategy and technical vision that powers digital products across the Orthopaedics Supply Chain. You will lead the Data Foundation initiative to modernize the current data landscape and build a scalable lakehouse architecture using Databricks and cloud technologies. In this role, you will drive architecture, engineering standards, governance, and execution to deliver trusted, reusable, and business-ready data products.

You will also provide technical leadership for business separation activities, ensuring that data architecture, pipelines, and platforms are designed to support future-state organizational needs while maintaining continuity, scalability, and delivery excellence.

This position requires strong leadership across architecture design, engineering governance, vendor delivery, and cross-functional collaboration to translate strategy into measurable business outcomes. If you are energized by building modern data capabilities that improve healthcare operations and enable better decisions at scale, this is an opportunity to make a meaningful impact.

Key Responsibilities:

• Lead the Data Foundation initiative to modernize the enterprise data ecosystem through a scalable lakehouse architecture and cloud-based data platform capabilities
• Define the data engineering strategy, target architecture, and reusable pipeline frameworks needed to deliver governed, high-quality data products
• Develop the strategy for a Data Supermarket that delivers business-ready data products for use across multiple functions.
• Translate complex business requirements and technical challenges into scalable architecture decisions and executable delivery plans
• Provide technical leadership for business separation activities, ensuring alignment to future-state operating models and platform continuity

• Establish and enforce best practices for:
• Data modeling (dimensional, Data Vault 2.0)
• Pipeline design, modularity, and reuse
• Engineering standards and quality controls

• Establish and scale data governance, data quality, and observability practices, including monitoring, lineage, reliability, and service-level expectations
• Define and implement automated testing strategies for data pipelines, including validation, data quality controls, and CI/CD integration

• Lead development and orchestration using Databricks, Python, SQL, dbt, Airflow, and cloud-native tools
• Partner with vendors and internal teams to manage delivery, enforce standards, and drive outcome-based execution
• Collaborate across Product, Supply Chain business, AI/ML, Data Governance, and IT teams to deliver measurable business impact

Qualifications

Education:

A Bachelor's or Master's degree in Computer Science, Engineering, Applied Mathematics, or in a related field.

Experience and Skills:

Required:

• Minimum of 8 years of experience in data engineering, including 2 or more years in leadership or people management roles
• Strong hands-on technical experience with:
• Databricks, PySpark, Spark SQL
• Python and SQL development
• Cloud platforms (Azure preferred, AWS acceptable)
• Proven expertise in:
• Modern data architecture and platform design
• Dimensional modeling and Data Vault 2.0
• Experience with:
• dbt, Airflow, Azure Data Factory (or equivalent tools)
• CI/CD pipelines, automation frameworks, and testing practices
• Required experience designing and implementing automated testing strategies for data engineering pipelines, including:
• End-to-end pipeline validation
• Data quality and integrity testing
• Integration with CI/CD pipelines
• Experience leading distributed teams and partnering effectively with external vendors and cross-functional stakeholders

Preferred:

• Experience supporting Agile product delivery teams and mentoring engineers in complex, fast-paced technical environments
• Familiarity with end-to-end supply chain domains such as planning, manufacturing, procurement, and distribution within MedTech or a similar regulated industry
• Knowledge of enterprise systems of record such as ERP, MES, and PLM, including experience working with fragmented or legacy data environments

• Experience with:
• Lakehouse architecture and Delta Lake
• Data observability and monitoring frameworks

• Experience collaborating with AI/ML and advanced analytics teams to enable scalable data and model-ready pipelines
• Knowledge of Power BI or enterprise BI platform
• Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to:
• Accelerate pipeline development
• Automate engineering workflows
• Exposure to code generation, pipeline automation, or low-code data engineering accelerators

Leadership Competencies

• Strong strategic thinking paired with a track record of execution excellence
• Ability to lead effectively in an outcome-driven, product-centric operating model
• Excellent communication, stakeholder management, and influencing skills across technical and business audiences
• Proven ability to translate complex architectures into executable delivery plans
• Focus on standardization, scalability, and engineering excellence
• This position may require up to 20% travel domestic and international

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via internal employees contact AskGS to be directed to your accommodation resource.

Required Skills:

Preferred Skills:

Advanced Analytics, Agility Jumps, Compliance Management, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Developing Others, Emerging Technologies, Execution Focus, Hybrid Clouds, Inclusive Leadership, Leadership, Resource Allocation, Team Management, Technical Development, Technologically Savvy

The anticipated base pay range for this position is :

$102,000.00 - $177,100.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).This position is eligible to participate in the Company's long-term incentive program.Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:Vacation –120 hours per calendar yearSick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year;