Lead, Ecosystem Engineer - MedTech Supply Chain Data

About the role

Johnson & Johnson is recruiting a Lead, Ecosystem Engineer in Bogotá to support the MedTech Supply Chain data ecosystem. Reporting to the Senior Manager, Ecosystem Product Owner, the role leads the physical engineering and implementation of secure, scalable, governed and reusable data capabilities that enable trusted data products and downstream business consumption. It works closely with the Ecosystem Product Owner, data product teams, architecture, platform engineering and governance stakeholders.

Key responsibilities

• Lead the detailed design, build, testing, deployment and ongoing support of data pipelines, transformations, integrations and data services.
• Translate functional requirements, data mappings, architecture standards and product priorities into engineering designs, specifications, delivery estimates and backlog items.
• Design and implement scalable ingestion, transformation, orchestration, storage and serving patterns for batch, streaming, API and event-driven use cases.
• Develop and maintain physical data models, schemas, transformation logic, interface contracts and reusable components.
• Set and enforce standards for source control, code review, automated testing, CI/CD, environment promotion, observability and documentation.
• Implement data quality controls, reconciliation checks, lineage capture, metadata integration, auditability and monitoring.
• Optimize workloads for reliability, scalability, performance and cost, and address technical debt and bottlenecks.
• Own release readiness, including test evidence, deployment plans, production validation, incident response and runbooks.
• Lead root-cause analysis of reliability issues and coordinate dependencies across data engineers, platform teams and source-system owners.
• Coach and guide engineers and delivery partners.

Required profile

• Bachelor's degree in computer science, engineering, information systems, data management or a related field; advanced degree preferred.
• Minimum 5 years of progressive experience in data engineering, software engineering, data platform delivery, systems integration, cloud data solutions or a related discipline.
• Hands-on experience with production-grade data pipelines, transformations, integrations and physical data models.
• Experience partnering with product owners, architects, platform teams, cybersecurity, privacy, governance and business stakeholders in a matrixed enterprise.
• Experience in a regulated healthcare, life sciences, medical technology, GxP, CSV or similar environment preferred.

Required skills

• Modern data platforms, distributed processing, cloud storage, orchestration, SQL, APIs, source control, automated testing and CI/CD.
• Operational monitoring, data quality controls, metadata, lineage, security, access controls and auditability.
• Preferred: cloud and lakehouse data engineering, data pipeline orchestration, physical data modeling, SQL, Python, DevOps, Agile delivery and secure engineering.