Manager Data Engineering

About the role

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.

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
• 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
• 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

Requirements

• 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)

Qualifications

• Education: A Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or in a related field
• 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

• Experience leading distributed teams and partnering effectively with external vendors and cross-functional stakeholders

Preferred Experience

• 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
• 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
• 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