Data Engineering Manager

Johnson & Johnson

Data Engineering Manager leading data strategy and execution at Johnson & Johnson. Shaping the enterprise data ecosystem for Orthopaedics Supply Chain.

Posted 7/22/2026full-timeRaynham • Florida, Massachusetts, New Jersey, Pennsylvania • 🇺🇸 United StatesSeniorLead💰 $102,000 - $177,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in modern data architecture, data engineering strategy, and scalable lakehouse solutions, with a strong focus on data quality, governance, and automated testing practices. Proven ability to lead cross-functional teams and deliver high-quality data products in complex environments.

Highest-signal resume keywords

Data Engineering LeadershipDatabricks DevelopmentCloud Platform ExpertiseAutomated Testing StrategiesData Governance Practices

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringDimensional ModelingData Vault 2.0CI/CD PipelinesAutomated TestingPython DevelopmentSQL DevelopmentLakehouse ArchitectureData Quality TestingData Observability

Soft Skills

Technical LeadershipCollaborationMentoringStakeholder ManagementAgile Methodologies

Tools & Technologies

DatabricksPySparkSpark SQLDbtAirflowAzure Data FactoryPower BIGitHub CopilotCursorCloud-Native Tools

Industry Keywords

Enterprise Data EcosystemData SupermarketSupply Chain DomainsMedTechERPMESPLMFragmented Data EnvironmentsAI/ML CollaborationAdvanced Analytics

Tech Stack

Tools & technologies

AirflowAWSAzureCloudERPPySparkPythonSparkSQLVault

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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 year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year