Sr Engineer Data Management

Job Description

Key Responsibilities

• Drive operational goals that directly support Data Management outcomes and enterprise data product delivery.
• Perform data profiling and analysis to identify quality trends, root causes, and opportunities for cleansing, standardization, and remediation.
• Deliver complex analyses that support data science, advanced analytics, and large-scale data mining initiatives.
• Identify and implement opportunities to automate manual processes, improve scalability, and strengthen operational efficiency.
• Design and deploy custom data solutions, programs, and platforms that address complex business and data science needs.
• Develop components of comprehensive data solutions aligned to customer expectations, business requirements, and technology standards.
• Coach junior colleagues on data management methods, engineering practices, operating processes, and role responsibilities.
• Apply Johnson & Johnson’s Credo and Leadership Imperatives in day-to-day collaboration, decision-making, and team engagement.

Qualifications

• · Bachelor’s degree in Computer Science, Information Systems, Data Science, Analytics, or a related field.
• · 6 to 7 years of experience in data engineering, data management, analytics, business intelligence, or related roles.
• · Working knowledge of AI-assisted analytics, GenAI concepts, and responsible AI practices.
• · Ability to apply responsible AI practices, including approved tool usage, sensitive data protection, and clear disclosure and traceability of AI-assisted outputs.
• · Hands-on experience designing, building, and maintaining data pipelines, integration processes, and analytical data assets.
• · Strong expertise in data quality management, including profiling, validation, cleansing, standardization, monitoring, and remediation.
• · Experience with Alteryx, advanced Tableau (programming), PowerApps, and Power BI, including data modeling and semantic layer design.
• · Proven ability to automate manual processes and scale data operations through improved workflows, tools, and governance practices.
• · Strong understanding of business process data models, enterprise data structures, and semantic layers.
• · Strong communication, collaboration, and stakeholder management skills, with the ability to translate technical concepts into business value.

Preferred Skills

• · Proficiency with SQL, Python, and modern data engineering frameworks.
• · Experience working with cloud data platforms such as Azure, AWS, or GCP.
• · Experience supporting enterprise data products, platforms, and reusable data assets.
• · Exposure to procurement business processes, data domains, and analytics use cases.
• · Experience applying AI, machine learning, or GenAI capabilities to data quality, data stewardship, or analytics use cases.