AI/ML Data Engineer (Databricks)

Ortho Clinical Diagnostics

Closes in 2 days Hybrid

Quick summary

Work type
Hybrid
Location
San Diego, CA
Salary
$70,000–$80,000 / yr
Posted
4 days ago
Closes
Jun 18, 2026 (soon)
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $189k
This role $75k
$50k most similar roles pay here $254k

This role pays less than 99% of similar roles. Most pay $151,716–$226,600 — the shaded band above. At the midpoint, this role pays about $75k versus about $189k for comparable roles.

Based on 240 similar postings.

Employer

About Ortho Clinical Diagnostics

Ortho Clinical Diagnostics is a global in-vitro diagnostics company providing testing solutions for blood screening, immunohematology, and clinical laboratory testing to improve patient outcomes. Industry: In-Vitro Diagnostics & Medical Devices

Ortho Clinical Diagnostics currently has 2 open roles on FindRole.

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At a glance

TL;DR · AI/ML Data Engineer (Databricks)

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Join QuidelOrtho as an AI/ML Data Engineer supporting the Global Data and Analytics team, where you will design and optimize data pipelines using Databricks for large-scale AI and machine learning initiatives. Your day-to-day responsibilities include collaborating with business stakeholders to identify high-value use cases, developing scalable Apache Spark-based data processing jobs, implementing ETL processes in Azure Data Factory, and ensuring the efficient deployment of ML solutions within Azure Machine Learning. You will also automate workflows using CI/CD pipelines through Azure DevOps while maintaining robust documentation for knowledge sharing across teams. This role requires expertise in Python, Scala, Databricks Delta Lake, and proficiency with tools like MLflow and Unity Catalog, all while adhering to data governance and security best practices in a cloud environment.

Skills

Databricks Azure Apache Spark Python Scala Azure Data Factory Azure Blob Storage Azure Synapse Analytics Databricks Delta Lake MLflow Azure DevOps CI/CD Data Governance Kafka Event Hubs

What you'll do

  • Design and develop scalable data pipelines using Databricks for AI/ML applications.
  • Work with business stakeholders to identify high-value AI/ML use cases and translate them into technical requirements.
  • Build Apache Spark-based data processing jobs in Databricks, optimizing performance and resource efficiency.
  • Implement ETL processes and orchestrate workflows using Azure Data Factory and integrate various data sources.
  • Ensure compliance with data security, governance, and best practices within Databricks and Azure environments.

What we're looking for

  • 1-3 years of experience in data engineering with focus on Databricks and AI/ML applications.
  • Expertise in Apache Spark and hands-on experience with Databricks for building scalable data pipelines.
  • Strong programming skills in Python and Scala for data engineering and machine learning workflows.
  • Experience with Azure Data Factory, Azure Data Lake, Blob Storage, and Synapse Analytics.
  • Proficiency with Databricks Delta Lake for optimizing data reliability and performance.
  • Knowledge of Azure DevOps for implementing CI/CD pipelines in Databricks-based projects.
  • Strong understanding of data governance, security practices, and compliance requirements.

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