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Omop Data Analyst Jobs (NOW HIRING)

UCLA Health

Data Analyst

Los Angeles, CA · On-site

$9.0K - $20K/mo

... Data Systems Analyst plays a key role in supporting clinical research through data integration ... Previous experience with OMOP modelling. * Strong knowledge of Tableau dashboards * Previous ...

NYULMC

Data Harmonization Analyst

New York, NY · On-site

Analyze source NAMs datasets (such as transcriptomics, proteomics, microscopy, imaging ... Experience with OMOP Common Data Model or other biomedical research CDMs Experience with ...

University of Rochester

$86K - $130K/yr

Regular Time Type: Full time Scheduled Weekly Hours: 40 Department: 900081 ISD Analytics Work Shift ... Experience with OMOP data model preferred * Master's degree preferred * Experience with integrating ...

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$82.6K

$136K

How much do omop data analyst jobs pay per year?

As of Aug 11, 2026, the average yearly pay for omop data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by OMOP Data Analysts when standardizing disparate healthcare datasets?

OMOP Data Analysts often encounter challenges in mapping and harmonizing diverse healthcare data sources into the OMOP Common Data Model. Variations in coding systems, data quality, and completeness can make the standardization process complex and time-consuming. Analysts must work closely with clinical experts and data engineers to ensure accurate transformation and validation of data, while also addressing issues like missing values or inconsistent terminologies. Collaboration and attention to detail are essential to maintaining data integrity and supporting reliable downstream analyses.

What are the key skills and qualifications needed to thrive as an OMOP Data Analyst?

To thrive as an OMOP Data Analyst, you need expertise in data analysis, knowledge of the OMOP Common Data Model, and experience with SQL and healthcare data, often supported by a degree in data science, informatics, or a related field. Familiarity with ETL tools, data transformation processes, and analytics platforms like R or Python, as well as experience with OHDSI tools, is essential. Strong problem-solving, attention to detail, and effective communication skills help you interpret complex data and collaborate with multidisciplinary teams. These competencies are crucial to ensure accurate data standardization, actionable insights, and improved decision-making in healthcare research.

What is an OMOP Data Analyst?

OMOP Data Analysts are professionals who specialize in working with healthcare data standardized to the OMOP (Observational Medical Outcomes Partnership) Common Data Model. They analyze, transform, and interpret large datasets from various sources to support research, clinical studies, and healthcare decision-making. Their expertise helps ensure data quality, consistency, and compliance with the OMOP model, enabling meaningful comparisons and insights across disparate healthcare datasets.
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Omop Data Analyst jobs near you
Infographic showing various Omop Data Analyst job openings in the United States as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

AI Solutions Engineer (Snowflake & Generative AI

Reign Mark Consulting Services, LLC

Princeton, NJ • On-site

Other

Posted 18 days ago

Job description

We are seeking a Senior AI Solutions Engineer to accelerate the development and productionalize of enterprise AI solutions within our Commercial Data & Analytics platform. This individual will be responsible for building AI-powered applications, semantic data models, and scalable data pipelines using Snowflake and modern Generative AI technologies.

The ideal candidate is a hands-on engineer with strong expertise in Snowflake, Python, SQL, and LLM-based application development who can quickly contribute to multiple high-priority AI initiatives.

Primary Responsibilities

•       Design and develop AI-powered applications using Snowflake Cortex, Large Language Models (LLMs), and Agentic AI frameworks.

•       Build and optimize semantic models and AI-ready datasets for structured and unstructured data.

•       Design and automate data ingestion, transformation, orchestration, and refresh pipelines.

•       Integrate clinical, commercial, and external data sources into enterprise AI workflows.

•       Optimize Snowflake performance and ensure production-ready, maintainable solutions.

•       Support deployment, testing, and operationalization of AI solutions.

Required Qualifications

•       7+ years of experience in Data Engineering, AI Engineering, or Software Engineering.

•       Strong hands-on experience with Snowflake, including Snowpark, SQL, and performance optimization.

•       Experience developing Generative AI applications using LLMs, Prompt Engineering, RAG, AI Agents, and workflow orchestration.

•       Strong programming skills in Python.

•       Experience designing semantic data models and enterprise data pipelines.

Preferred Qualifications

•       Experience with Snowflake Cortex (Analyst, Search, Complete, Intelligence, Cortex Agents).

•       Experience with healthcare or life sciences data.

•       Experience with OMOP, claims data, clinical trial data, or commercial pharmaceutical data.

Technical Skills

•       Snowflake (Snowpark, Cortex, SQL)

•       Python

•       Generative AI / LLMs

•       RAG & AI Agents

•       Prompt Engineering

•       Semantic Modeling

Nice-to-Have Experience

•       Commercial Pharma Analytics

•       Clinical Trials

•       Claims Data

•       OMOP Data Model

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