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.
Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Business IntelligenceJob Category:
ProfessionalAll Job Posting Locations:
Pune, Maharashtra, IndiaJob Description:
Job Description: Sr Analyst – Data & Analytics
Data Engineering with Applied AI | 5–7 Years of Experience
Role Overview
We are seeking a Data Engineer with 5–7 years of experience in building scalable data platforms and preliminary hands-on exposure to AI solutions.
Key Responsibilities
· Develop and automate high-performance data processing systems to drive business growth and improve product experience.
· Translate business requirements into technical solutions with end-to-end ownership.
· Promote high-quality software engineering practices for building data infrastructure and pipelines at scale.
· Build reliable, efficient, testable, and maintainable data pipelines.
· Design and develop data pipelines using metadata-driven ETL tools and open-source data processing frameworks.
· Provide production support, resolve high-priority incidents, and troubleshoot development and coding issues.
· Work with cross-functional teams to enable insights across the data lifecycle.
AI Responsibilities
· Support data pipelines and data preparation for AI and Generative AI applications.
· Build and maintain integrations with Azure OpenAI and other Azure AI services.
· Develop and support RAG (Retrieval-Augmented Generation) workflows, including document ingestion, embeddings, and search indexing.
· Collaborate with business and technical teams to implement AI-enabled solutions and enterprise copilots.
· Ensure AI solutions adhere to data governance, security, privacy, and Responsible AI standards.
Minimum Qualifications
· 5–7 years of experience in data engineering, including SQL-based design and development of scalable, robust data pipelines.
· Experience with large-scale data lake and data engineering projects.
· Proficiency in advanced SQL and SQL performance tuning.
· Strong experience in Python or another programming language used to process large datasets.
· Experience with ETL/ELT, data modeling, STAR schemas, metadata management, data quality, and production support.
· Working knowledge of REST APIs, JSON, authentication patterns, and integration of cloud-based services.
· Foundational understanding of machine learning and Generative AI concepts, including large language models, embeddings, vector search, prompt engineering, and RAG.
· Ability to troubleshoot end-to-end data and AI pipelines and work with users to resolve issues.
Preferred Qualifications
· BE- Computer Science with healthcare exposure.
· Experience with AWS data technologies such as Amazon S3 or Amazon Redshift is beneficial where relevant to the existing data landscape.
· Basic understanding of LLMs, Prompt Engineering, Embeddings, Vector Search, and RAG concepts.
· Exposure to Azure OpenAI Service, Azure AI Search, Azure Databricks, or Azure Machine Learning.
· Experience working on chatbot, copilot, or AI assistant solutions is preferred.
· Familiarity with frameworks such as Semantic Kernel, LangChain, or similar orchestration tools.
Required Skills:
Preferred Skills:
Advanced Analytics, Analytical Reasoning, Business Behavior, Business Intelligence (BI), Cross-Functional Collaboration, Data Analysis, Data Integration, Data Modeling, Data Privacy Standards, Data Reporting, Detail-Oriented, Management Systems Implementation, Problem Solving, Process Oriented, Project Management, Statistical Analysis Systems (SAS) Programming, Workflow Analysis