Manager, Data Platform

Johnson & Johnson

. Own and implement the Data Platform and Data Foundation strategy, target architecture, roadmap, engineering standards, and measurable outcomes .

Posted 10/19/2026full-timeUnited StatesMid-LevelSenior💰 $102,000 - $177,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Platform Strategy, Architecture, and Engineering Governance, with a strong focus on Databricks, Data Ingestion Frameworks, and Automated Testing. Proven ability to lead teams, implement data observability, and translate business needs into actionable platform capabilities.

Highest-signal resume keywords

Databricks ExpertiseData Pipeline Framework DesignAutomated Testing StrategiesData Architecture and ModelingCloud Data Services Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DatabricksPySparkSpark SQLPythonSQLDelta LakeData ModelingAutomated TestingData GovernanceData Observability

Soft Skills

Technical LeadershipCommunicationInfluencing DecisionsPeople ManagementCollaboration

Tools & Technologies

Azure Data FactoryAWS GlueApache AirflowDbtFivetranPower BIAI/ML PlatformsGitHub CopilotCursorClaude Code

Industry Keywords

Data EngineeringLakehouse ArchitectureMedTechRegulated IndustrySelf-Service Analytics

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudERPPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Own and implement the Data Platform and Data Foundation strategy, target architecture, roadmap, engineering standards, and measurable outcomes
Lead the design and evolution of a scalable Databricks lakehouse using medallion architecture, reusable data products, and cloud-native services
Design, build, and scale reusable, metadata-driven data ingestion and data pipeline frameworks
Establish platform engineering standards for data modeling, code quality, automated testing, CI/CD, documentation, security, performance, cost efficiency, and production readiness
Design and implement the data engineering governance framework with Data Governance
Embed ownership, business definitions, policy controls, architecture reviews, data quality, certification, lineage, and traceability into engineering workflows and data products
Implement end-to-end data observability and operational governance, including monitoring, reliability, service-level expectations, incident prevention, and lifecycle management
Enable analytics and AI teams with governed, reusable, and AI-ready data
Provide technical governance and architectural oversight for business separation and transition activities
Translate business and digital-product needs into platform capabilities, work packages, delivery roadmaps, and outcome-based execution plans
Lead internal engineers and delivery partners; set technical direction, review solution quality, dependencies, and risks, and build sustainable internal capability

Requirements

What you’ll need

Minimum of a Bachelor’s degree and/or equivalent University degree required
Minimum of six (6) years of relevant professional work experience
Multifaceted experience in data engineering or data platforms, including technical leadership, people management, or platform ownership
Experience leading the design, implementation, or modernization of a data platform or lakehouse and converting strategy into an executable roadmap
Strong hands-on expertise with Databricks, PySpark, Spark SQL, Python, SQL, Delta Lake, and cloud data services
Azure and/or AWS experience
Experience designing reusable ingestion and data pipeline frameworks, including orchestration and integration with dbt, Apache Airflow, Azure Data Factory, AWS Glue, or comparable tools
Strong knowledge of data architecture and modeling, including dimensional modeling, star and snowflake schemas
Experience defining and implementing automated testing strategies for data engineering code and pipelines
Experience establishing engineering governance, coding standards, release controls, documentation expectations, architecture reviews, and production-readiness practices
Experience implementing data observability across pipelines and products, including monitoring, lineage, reliability, alerting, and service-level management
Experience leading distributed teams and governing external vendors or managed-service partners
Ability to communicate sophisticated platform concepts to technical and business collaborators and influence decisions in a matrixed organization
Preferred: focused degree in Computer Science, Engineering, Applied Mathematics, Information Systems, or related field
Preferred: Master’s degree
Preferred: Fivetran or similar managed data integration and change-data-capture platforms
Preferred: federated business teams, self-service analytics, certified data products, and AI-ready consumption patterns
Preferred: end-to-end supply chain domains within MedTech or another regulated industry
Preferred: ERP, MES, PLM, and planning platforms
Preferred: Power BI, semantic models, data marketplaces or catalogs, and AI/ML platforms
Preferred: web and digital application architecture, APIs, integration patterns, and vendor-led application delivery
Preferred: AI-assisted engineering tools such as GitHub Copilot, Cursor, or Claude Code
Preferred: Agile product teams, mentoring engineers, and reusable platform capabilities
Required to work onsite 1 to 3 days per week
May be required to travel up to 20% domestically and internationally

Benefits

Comp & perks

Consolidated retirement plan (pension)
Savings plan (401(k))
Long-term incentive program
Vacation – 120 hours per calendar year
Sick time – 40 hours per calendar year; 48 hours for Colorado employees; 56 hours for Washington employees
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 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