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Remote Azure Data Factory Jobs in Irvine, CA (NOW HIRING)

Western Digital

Senior Mac Engineer

Irvine, CA · On-site +1

$112K - $154K/yr

Together, we can build the future of data storage. We are seeking a highly skilled Senior Mac ... Integrate Apple devices into enterprise identity platforms (Azure AD / Entra ID) * Implement and ...

Western Digital

Senior Mac Engineer

Irvine, CA · On-site +1

$112K - $154K/yr

Together, we can build the future of data storage. We are seeking a highly skilled Senior Mac ... Integrate Apple devices into enterprise identity platforms (Azure AD / Entra ID) * Implement and ...

EnerSys

Senior Finance AI & Automation Developer

Chino, CA · On-site +1

$95K - $142K/yr

Remote * Tuesday-Thursday: Onsite at our Reading, PA location Candidates outside the Reading, PA ... Azure experience required * Strong understanding of data structure and APIs required * Experience ...

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How much do remote azure data factory jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for remote azure data factory in Irvine, CA is $62.69, according to ZipRecruiter salary data. Most workers in this role earn between $56.78 and $70.43 per hour, depending on experience, location, and employer.

What is a remote Azure Data Factory professional?

A Remote Azure Data Factory professional is an IT specialist who designs, builds, and manages data integration solutions using Microsoft Azure Data Factory while working from a remote location. They create and manage data pipelines to move and transform data between various sources and destinations in the cloud. These professionals often collaborate with data engineers, analysts, and business stakeholders to ensure data is accessible, secure, and reliable for analytics and reporting needs.

What are some common challenges faced by remote Azure Data Factory professionals, and how can they be addressed?

Remote Azure Data Factory professionals often encounter challenges related to communication and collaboration, especially when integrating data from multiple sources across different teams. To address this, it's essential to establish clear documentation practices, utilize collaboration tools such as Microsoft Teams, and schedule regular check-ins with stakeholders. Additionally, proactively managing data pipeline failures and ensuring security compliance in a remote setting requires strict adherence to best practices and close coordination with IT and security teams. Building a strong support network and maintaining open lines of communication are key to overcoming these challenges and succeeding in the role.

What are the key skills and qualifications needed to thrive as a remote Azure Data Factory engineer, and why are they important?

To thrive as a Remote Azure Data Factory Engineer, you need strong expertise in data integration, ETL processes, and cloud-based data solutions, typically supported by experience in Microsoft Azure and a relevant technical degree. Proficiency in Azure Data Factory, SQL, Power BI, and familiarity with other Azure services or certifications (such as Azure Data Engineer Associate) is highly beneficial. Excellent problem-solving, communication, and time management skills are crucial for effective remote collaboration and troubleshooting. These competencies ensure efficient data pipeline development, seamless data flow, and the ability to deliver robust analytics solutions in distributed environments.

What is the difference between Remote Azure Data Factory vs Remote Data Engineer?

AspectRemote Azure Data FactoryRemote Data Engineer
CredentialsAzure certifications, data integration skillsData engineering certifications, cloud platform knowledge
Work EnvironmentCloud-based, primarily using Azure platformCloud and on-premises environments, broader tech stack
Industry UsageData integration, ETL workflows in AzureData pipeline development, database management
Search & Comparison IntentFocus on specific tool (Azure Data Factory)Broader data engineering roles

Remote Azure Data Factory specialists focus on designing and managing data workflows within the Azure platform, often requiring specific certifications. Remote Data Engineers have a broader scope, building and maintaining data pipelines across various environments. While both roles involve data integration, Azure Data Factory roles are more tool-specific, whereas Data Engineers encompass a wider range of technologies and responsibilities.

What are the most commonly searched types of Azure Data Factory jobs in Irvine, CA?

The most popular types of Azure Data Factory jobs in Irvine, CA are:

What are popular job titles related to Remote Azure Data Factory jobs in Irvine, CA?

For Remote Azure Data Factory jobs in Irvine, CA, the most frequently searched job titles are:

What job categories do people searching Remote Azure Data Factory jobs in Irvine, CA look for?

The top searched job categories for Remote Azure Data Factory jobs in Irvine, CA are:

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Cities near Irvine, CA with the most Remote Azure Data Factory job openings:

Remote Azure Data Factory jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Pomona, CA • Remote

Full-time

Re-posted 17 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply