Data Product Lead

About this role

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world.  We provide an inclusive work environment where each person is considered as an individual.  At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function: Technology Product & Platform Management

Job Sub Function: Technical Product Management

Job Category: Scientific/Technology

All Job Posting Locations: New Brunswick, New Jersey, United States of America

Job Description: Position Summary

We are searching for the best talent for a Data Product Lead to be located in New Brunswick, NJ and São José dos Campos.

Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s): New Brunswick, NJ and São José dos Campos, Brazil.

São José dos Campos, Brazil - Requisition Number: R-095121

Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.

The IT Lead – Technical Product Owner, Data Enablement is an experienced individual contributor responsible for building, operating, and continuously improving core data platform and data quality capabilities used across Corporate Business Technology (CBT) . This role supports enterprise analytics, reporting, and AI use cases by helping ensure data platforms are reliable, secure, cost‑aware, and easy to use. The role works closely with business stakeholders, engineering teams, platform partners, and governance leaders to enable teams to produce high‑quality data products with confidence. This position focuses on hands‑on delivery, platform reliability, and practical enablement . Success is measured by platform adoption, consistency of standards, and improved trust in data. Key Responsibilities Data Platform Enablement • Support the technical ownership and day‑to‑day operation of enterprise data platforms , including the Databricks Intelligence Platform. • Implement and maintain platform standards, patterns, and reusable components for data ingestion, transformation, and consumption. • Apply and support medallion (Bronze, Silver, Gold) patterns , including guidance for schema design, performance, and data lifecycle management. • Partner with infrastructure and platform teams to ensure environments are stable, secure, and ready for production use.

Data Quality Products & Trust Enablement • Contribute to the implementation and support of enterprise data quality tools and frameworks . • Help design and apply data quality checks such as validation rules, completeness checks, freshness monitoring, and reconciliation. • Work with data owners and governance partners to translate quality requirements into practical technical solutions . • Support transparency into data quality signals and promote consistent use of quality checks within pipelines.

Pipeline Implementation & Support • Build and support batch and streaming data pipelines that align to platform and quality standards. • Assist teams in adopting near‑real‑time and event‑driven patterns where appropriate. • Ensure pipelines include common capabilities for monitoring, failure handling, and data validation.

Reliability, Operations, and Cost Awareness • Partner with Technology Services to support platform reliability , monitoring, and incident response. • Contribute to operational dashboards, alerts, and basic runbooks. • Help teams understand and apply cost‑aware usage patterns for compute, storage, and data movement. • Assist with solving performance, stability, and data issues.

Engineering Practices & Security • Follow and support sound engineering practices , including version control, CI/CD, testing, and infrastructure‑as‑code where applicable. • Ensure platform implementations align with security, privacy, and access control requirements. • Support audit-ability and traceability through logging, metadata, and lineage capture.

Collaboration & Continuous Improvement • Work closely with engineers, platform managers, and product partners to deliver platform improvements. • Translate platform guidance into clear technical steps and examples. • Share findings, patterns, and documentation to help teams adopt platform capabilities more easily. • Actively look for ways to improve platform usability, reliability, and developer experience.

Required Qualifications • Bachelor’s degree in computer science, Engineering, Information Systems, or related field • 5–7+ years of experience in data engineering, analytics platforms, or data infrastructure roles. • 3+ Years of hands‑on experience working with modern data platforms or Lakehouse technologies (such as Databricks or similar). • Experience implementing data ingestion, transformation, and validation in production systems. • Familiarity with data quality concepts and tools , including rule‑based validation and monitoring. • Working knowledge of CI/CD, infrastructure‑as‑code, and secure engineering practices. • Ability to collaborate effectively across teams. • Clear written and verbal communication skills.

Preferred Qualifications • Experience supporting or operating enterprise data quality platforms . • Exposure to data catalog, metadata, or lineage tools. • Experi

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