Senior IT Analyst - Data Engineering

Johnson & Johnson Innovative Medicine•Irvine, CA

3d•$92,000 - $148,350

About The Position

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. We’re seeking a hands-on Senior IT Analyst - Data Engineering, with experience in the Microsoft data & cloud ecosystem and a clear focus on operationalizing AI. The role will involve design, build, and run scalable data platforms and inference pipelines that enable analytics, ML model training and production inference. You’ll work closely with data and software engineers, product owners and IT/security teams. The role is located in Irvine, CA.

Requirements

Bachelor's Degree required, with a strong preference for a Master's Degree.
Cloud & AI/ ML Technologies: Experience operationalizing predictive models. Refining Projections and establishing model packaging, deployment, inference pipelines and monitoring. Build, validate, and deploy predictive models to forecast sales, case coverage, and customer adoption of NPI’s.
Use advanced analytics to identify cannibalization trends, competitive conversions opportunities, and build resource allocation recommendations across geographical locations
Data Pipelines (ETL/ ELT): 1-2 years in data engineering, ETL, platform engineering experience. Build, test, and enhance robust data ingestion pipelines from SQL
Database Management: Experience with Microsoft/Azure data stack: Azure Data Factory, Azure Databricks, Azure Data Lake Storage (ADLS), Azure SQL / SQL Server.
Programming and Scripting: Strong programming skills in Python and/or PySpark; familiarity with SQL as primary query language. Write complex, efficient SQL queries, maintain relational database integrity, and design table schemas.
Data Modeling: Good interpersonal skills and experience working in multi-functional agile teams. Structure data for optimal performance in data warehouses or data lakes.
Strong analytical and troubleshooting skills; Develop scalable data pipelines from sales systems and SFDC to support strategic decision-making and operational efficiency. Leverage AI-driven insights to align with organizational Sales strategies and case coverage models.
Use storytelling techniques to communicate complex insights clearly to executive leadership and partners.
Data Compliance: Demonstrable understanding of data governance, security controls, access management and compliance. Work with data scientists and analysts to ensure data quality and availability.

Nice To Haves

Working knowledge of AL data models, LLMs Azure Machine Learning, MLOps frameworks and feature stores.
Experience with Power BI, Copilot Semantic models or other BI tools for delivering analytical solutions.
Familiarity with Azure Cognitive Services, Azure OpenAI integration, and prompt engineering patterns.
Knowledge of Responsible AI toolkits and regulatory frameworks.

Responsibilities

Design, build and operate scalable ETL/ELT pipelines using Microsoft/Azure technologies (SQL Server, Databricks, AWS Redshift).
Implement data ingestion, transformation, and integration patterns for structured and unstructured data.
Build and maintain production-ready model scoring and inference pipelines; integrate ML models into data platforms and applications.
Implement CI/CD, infrastructure-as-code and automated deployment for data workflows and model artifacts.
Ensure data quality, lineage and governance (cataloging, metadata, data masking, retention) in collaboration with data governance teams.
Operate and monitor data platforms and models: logging, alerting, performance tuning and cost optimization.
Collaborate on data modeling and architecture decisions (data warehouse, star/snowflake schemas, Delta Lake or equivalent).
Apply Responsible AI principles: bias checks, model explainability, monitoring and compliance controls.
Working knowledge of Jupyter Notebook.
Implement Natural Language Processing (NLP) techniques to enhance data interpretation and drive insights from unstructured text data within structured datasets.
Develop and maintain SQL agents to automate data retrieval and manipulation, ensuring the efficient flow of information for analysis and reporting.

Benefits

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
- Vacation –120 hours per calendar year
- Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
- Holiday pay, including Floating Holidays –13 days per calendar year
- Work, Personal and Family Time - up to 40 hours per calendar year
- Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
- Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
- Caregiver Leave – 80 hours in a 52-week rolling period10 days
- Volunteer Leave – 32 hours per calendar year
- Military Spouse Time-Off – 80 hours per calendar year