Lead Data Engineer

Johnson & Johnson - Raritan, NJ

Full-time - Senior

Raritan, NJ

10,001+ employees

Chemical Manufacturing

About the position

The Lead Data Engineer at Johnson & Johnson is responsible for the technical design and implementation of data and analytics solutions across various business areas. This role involves collaborating with business technology partners to drive innovative data products, shaping overall solution architecture, and ensuring best practices are followed to optimize business outcomes. The position requires a strong technical background in data engineering and cloud environments, with a focus on delivering scalable data pipelines and optimizing data solutions for performance and cost savings.

Responsibilities

• Collaborate with Business Technology partners to understand existing solutions/products, business needs and priorities.
• Shape solution design in alignment with overall business strategy and Technology Service's roadmap.
• Design, develop and deliver scalable data pipelines that process large datasets for business intelligence, data science and more.
• Optimize data solutions and infrastructure for improved performance, reliability, and cost savings.
• Act as a consultant to other teams, challenge the status quo, market the team's products, and provide technical leadership in the Data Solutions space.
• Understand and articulate the benefits of reusable patterns and products developed by the team to potential adopters.
• Stay updated with industry trends and advancements in data engineering and analytics to provide recommendations to stakeholders.

Requirements

• A minimum of a bachelor's degree in Computer Science, Information Technology or a related field.
• A minimum of 5 years of professional experience in data engineering.
• Strong problem-solving skills with the ability to analyze complex data and develop innovative solutions.
• Good communication and interpersonal skills for collaboration with clients and team members.
• Technical experience building data pipelines and managing Cloud environments.

Nice-to-haves

• Generative AI (Prompt Engineering, RAG, Azure OpenAI, Amazon Bedrock, etc.)
• Data Visualization (Power BI, Tableau, etc.)
• Agile Processes (Scrum, Kanban)
• DevOps / CI-CD / MLOps

Benefits

• Flexible work arrangements
• Career development opportunities
• Health and wellness programs