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Data Management: * Collect, preprocess, and analyze large datasets for training and validating AI ... Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies ...
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Machine Learning Engineer New Grad 2024-2025 -Remote
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... SOA, BPM, Data Warehousing, SharePoint Consulting and IT Infrastructure. Our other offerings ... Developer (100 % remote) Duration : 6 months Location : Peoria, IL Need GC and USC : Top Three ...
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Digital Chemistry Specialist - Remote
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Remote Azure Data Engineer information
See Peoria, IL salary details
$43.7K - $55.5K
0% of jobs
$55.5K - $67.4K
1% of jobs
$67.4K - $79.3K
3% of jobs
$79.3K - $91.1K
4% of jobs
$91.1K - $103K
7% of jobs
$113.4K is the 25th percentile. Wages below this are outliers.
$103K - $114.8K
11% of jobs
$114.8K - $126.7K
12% of jobs
The median wage is $129.9K / yr.
$126.7K - $138.6K
45% of jobs
$138.6K - $150.4K
8% of jobs
$150.4K - $162.3K
5% of jobs
$162.3K - $174.2K
3% of jobs
$43.7K
$127.3K
$174.2K
How much do remote azure data engineer jobs pay per year?
What are some common challenges a remote Azure Data Engineer might face, and how are they typically addressed?
A common challenge for Remote Azure Data Engineers is ensuring secure, reliable data transfer and integration across distributed systems while collaborating with teams that may be in different time zones. This is typically addressed by implementing best practices for cloud security, employing automated monitoring, and leveraging project management tools to stay aligned with cross-functional teams. Clear, proactive communication is essential in a remote environment, as is documentation to keep everyone updated on project progress. Many organizations also offer regular virtual check-ins and access to knowledge-sharing platforms to foster collaboration. By staying organized and proactive, remote Azure Data Engineers can successfully deliver scalable data solutions in a distributed work setup.
What is a remote Azure Data Engineer?
A Remote Azure Data Engineer is responsible for designing, implementing, and managing data solutions using Microsoft Azure cloud services while working from a remote location. They work with tools like Azure Data Factory, Azure SQL Database, and Azure Synapse Analytics to process, store, and analyze data. Their role includes data pipeline development, performance optimization, and ensuring data security. Collaboration with data scientists, analysts, and business teams is common to support data-driven decision-making.
What are the key skills and qualifications needed to thrive as a remote Azure Data Engineer?
To thrive as a Remote Azure Data Engineer, you need expertise in designing, implementing, and managing data solutions using Microsoft Azure, along with proficiency in SQL, data warehousing, and ETL processes. Familiarity with tools like Azure Data Factory, Azure SQL Database, Databricks, and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly valued. Strong problem-solving skills, effective communication, and the ability to work autonomously make candidates stand out in this remote role. These skills ensure that data pipelines are robust, secure, and scalable, enabling organizations to make data-driven decisions efficiently.

Full-time
Re-posted 18 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 Descriptionโ
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:
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Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.
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Integrate pre-trained models or build custom models for specific use cases.
Automation Design and Development:
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Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.
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Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.
Data Management:
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Collect, preprocess, and analyze large datasets for training and validating AI models.
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Ensure data privacy and compliance with regulatory requirements during data handling.
System Integration:
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Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.
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Build and maintain pipelines for real-time AI inference and automation.
Monitoring and Optimization:
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Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.
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Optimize models and processes based on performance metrics and user feedback.
Research and Innovation:
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Stay updated with the latest advancements in Generative AI and automation technologies.
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Identify opportunities for implementing cutting-edge AI solutions to address business challenges.
Documentation and Collaboration:
-
Document technical designs, workflows, and implementation strategies.
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Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.
Required Qualifications:
-
Bachelorโs or Masterโs degree in Computer Science, Engineering, or a related field.
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Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.
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Proficiency in designing and deploying machine learning models, particularly in Generative AI.
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Experience with automation tools (e.g., RPA, workflow orchestration tools).
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Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).
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Solid understanding of data structures, algorithms, and software design principles.
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Strong analytical and problem-solving skills.
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Excellent communication and teamwork abilities.
Preferred Qualifications:
-
Experience with NLP, image generation, or multimodal AI models.
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Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.
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Familiarity with prompt engineering and fine-tuning Generative AI models.
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Knowledge of MLOps practices for deploying and maintaining AI solutions.
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Previous experience in automation or workflow optimization projects.
Why Join Us?
-
Work with cutting-edge Generative AI technologies.
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Collaborate with a team of forward-thinking innovators.
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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.
About EnthuZiastic
Sourced by ZipRecruiter
Industry
E-learning
Company size
11 - 50 Employees
Headquarters location
San Jose, CA, US
Year founded
2020