• Job title Sr. Data Engineer
• Function Data Analytics & Computational Sciences
• Sub function Data Engineering
• Category Experienced Engineer, Data Engineering (ST5)
• Location Alajuela / Costa Rica
• Date posted Apr 09 2026
• Requisition number R-068931
• Work pattern Hybrid Work

Description

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.

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Job Description:

Johnson & Johnson is hiring for a Sr. Data Engineer to join our team located in Shockwave Medical Costa Rica.

Position Overview

This role will focus primarily on enabling self-service analytics and developing high-quality dashboards, reports, and data models in Power BI. You will partner closely with business stakeholders to translate analytical needs into robust, scalable semantic models and intuitive dashboards. This is an ideal role for someone who blends strong technical data modeling skills with design thinking, business understanding, and a passion for delivering data experiences that drive decision-making.

Essential Job Functions

• Design, develop, and maintain Power BI dashboards, reports, and reusable templates that deliver actionable insights to stakeholders.
• Build Power BI semantic data models (import/direct query/aggregation tables), ensuring optimized performance and scalability.
• Develop reusable DAX measures, calculations, and model components following best practices.
• Implement row-level security, workspace governance, and deployment pipelines.
• Translate business requirements into robust data model’s leveraging Snowflake tables curated by the broader Data Engineering team.
• Collaborate with Snowflake, dbt/Coalesce, Fivetran, and Databricks teams to ensure data readiness for analytics consumption.
• Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts.
• Maintain documentation for reports, datasets, and analytical workflows.
• Implement data quality checks and monitoring processes to ensure data accuracy and consistency.
• Stay up to date on the latest trends and technologies in the modern data stack (Power BI, Snowflake, Fivetran, Coalesce, etc.).

Requirements

• Bachelor’s degree in systems Engineering or similar fields.
• 5+ years of experience in data analytics, BI engineering, or analytics engineering roles.
• Expert-level proficiency with Power BI (primary)—including DAX, data modeling, Power Query, performance optimization, workspaces, deployment pipelines, and governance
• Strong knowledge of Snowflake, SQL, Python. Familiarity with dbt/Coalesce, Databricks, and Fivetran is a plus.
• Experience integrating data from enterprise applications (e.g., Oracle Fusion Cloud, Salesforce, Adaptive Planning) is a plus
• Ability to translate complex business needs into intuitive dashboards with strong data storytelling.
• Strong analytical thinking and problem-solving abilities.
• Familiarity with data governance, data quality, and data catalog tools.
• Understanding of UX best practices for dashboard layout, design, and usability.
• Ability to work independently and as part of a team.
• Interpersonal and communication skills to collaborate effectively with business partners and cross-functional teams.
• Strong strategic mindset with the ability to align analytics initiatives with overall business goals and proactively identify opportunities for leveraging data to drive business value

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