Johnson & Johnson
Senior IT Analyst - Data Engineering
Salary
-
Job type
Full-time
Location
Irvine, California, US
Remote
No
Posted
4 days ago
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View resume exampleJob 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
Technology Product & Platform Management
Job Sub Function
Platform/Cloud Engineering
Job Category
Scientific/Technology
All Job Posting Locations
Irvine, California, United States of America
Job Description
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.
Key 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.
Required Qualifications & Experience
- 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 and 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.
Nice-to-have
- 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.
- 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.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
#JNJTECH
Required Skills
Preferred Skills
The anticipated base pay range for this position is
$92,000.00 - $148,350.00
Additional Description For Pay Transparency
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)).
Benefits
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
For additional general information on Company benefits, please go to: https://www.careers.jnj.com/employee-benefits
Responsibilities
- 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
- 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
- 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
- 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
- Build, test, and enhance robust data ingestion pipelines from
- SQL and Database Management: Experience with Microsoft/Azure data stack: Azure Data Factory, Azure Databricks, Azure Data Lake Storage (ADLS), Azure SQL / SQL Server
- 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
Qualifications
- Working knowledge of Jupyter Notebook
- Bachelor's Degree required, with a strong preference for a Master's Degree
- Cloud & AI/ ML Technologies: Experience operationalizing predictive models
- Data Pipelines (ETL/ ELT): 1-2 years in data engineering, ETL, platform engineering experience
- 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;
- 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
- 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
Benefits
- $92,000.00 - $148,350.00
- 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))
- 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
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