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Johnson & Johnson

Data Engineering Manager

Johnson & Johnson

Data Engineering Manager at Johnson & Johnson focusing on healthcare innovation through scalable data solutions. Leading initiatives to modernize data architecture and improve organizational decision-making.

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

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in modern data architecture, data engineering strategy, and scalable lakehouse architecture, 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 that drive business impact.

Highest-signal resume keywords
Data Engineering LeadershipDatabricks DevelopmentAutomated Testing StrategiesCloud Platform ExpertiseData Governance Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data EngineeringDimensional ModelingData Vault 2.0CI/CD PipelinesEnd-to-End Pipeline ValidationData Quality TestingPython DevelopmentSQL DevelopmentPySparkSpark SQL
Soft Skills
Technical LeadershipCollaborationStakeholder ManagementProblem SolvingCommunication
Tools & Technologies
DatabricksDbtAirflowAzure Data FactoryCloud-Native Tools
Industry Keywords
Data EcosystemData GovernanceData QualityData ProductsBusiness Separation Activities

Tech Stack

Tools & technologies
AirflowAWSAzureCloudPySparkPythonSparkSQLVault

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
  • 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

Benefits

Comp & perks
  • 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