Data Platform Manager

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 Engineering, including the design and implementation of scalable Data Platforms and Lakehouses using Databricks and cloud services. Proficient in establishing engineering governance, automated testing strategies, and data observability to ensure high-quality, AI-ready data products.

Highest-signal resume keywords

Data Engineering LeadershipDatabricks ExpertiseCloud Data Services (Azure/AWS)Data Pipeline Framework DesignAutomated Testing Strategies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

DatabricksPySparkSpark SQLPythonSQLDelta LakeData ArchitectureAutomated TestingData ModelingData Governance

Soft Skills

Technical LeadershipCommunicationInfluencing DecisionsMentoring EngineersCollaboration

Tools & Technologies

Apache AirflowAzure Data FactoryAWS GlueFivetranPower BIAI/ML PlatformsGitHub CopilotCursorClaude CodeCI/CD Tools

Certifications & Qualifications

Bachelor’s DegreeMaster’s Degree (Preferred)

Industry Keywords

MedTechSupply ChainERPMESPLMData IntegrationChange Data CaptureDigital Application ArchitectureAgile MethodologiesData Quality

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 ingestion and data pipeline frameworks
Establish 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 workflows and data products
Implement end-to-end data observability and operational governance
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 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
Focused degree in Computer Science, Engineering, Applied Mathematics, Information Systems, or related field preferred
Master’s degree preferred
Minimum of six (6) years of relevant professional work experience
Experience in data engineering or data platforms, including technical leadership, people management, or platform ownership
Experience leading 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, including unit, integration, regression, reconciliation, data-quality testing, and CI/CD integration
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 experience with Fivetran or similar managed data integration and change-data-capture platforms
Preferred experience building federated, self-service, certified-data-product, and AI-ready platforms
Familiarity with supply chain domains within MedTech or another regulated industry
Knowledge of ERP, MES, PLM, and planning platforms
Experience integrating with Power BI, semantic models, data marketplaces or catalogs, and AI/ML platforms
Understanding of web and digital application architecture, APIs, integration patterns, and vendor-led application delivery
Experience using AI-assisted engineering tools such as GitHub Copilot, Cursor, Claude Code, or similar
Experience supporting Agile product teams, mentoring engineers, and building reusable platform capabilities
Ability to work onsite 1 to 3 days per week
Ability to travel up to 20% domestically and internationally

Benefits

Comp & perks

Consolidated retirement plan (pension)
401(k) savings plan
Long-term incentive program
Vacation – 120 hours per calendar year
Sick time – 40 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
Hybrid work arrangement
Inclusive interview accommodations
Travel opportunities up to 20% domestically and internationally