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Analytics Engineer Remote Dbt Jobs in Jenison, MI

Kiongroup

Simulation Engineer

Grand Rapids, MI · On-site +1

$65K - $140K/yr

... and remote flexibility. You'll help design the future of warehouse automation by developing ... The ideal candidate has experience with simulation modeling, strong analytical and statistical ...

Kiongroup

Simulation Engineer

Grand Rapids, MI · On-site +1

$65K - $140K/yr

... and remote flexibility. You'll help design the future of warehouse automation by developing ... The ideal candidate has experience with simulation modeling, strong analytical and statistical ...

CFS

Oracle Fusion Integrations Engineer

Hudsonville, MI · On-site +1

$156K/yr

Location: Remote or Hybrid (company based in West Michigan) Job Overview: The Oracle Fusion ... Strong analytical, troubleshooting, and stakeholder communication skills * Experience with REST ...

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All JobsAnalytics Engineer Dbt JobsAnalytics Engineer Remote Dbt JobsAnalytics Engineer Remote Dbt Jobs in Jenison, MI

Analytics Engineer Remote Dbt information

See Jenison, MI salary details

$32.5K

$87.6K

$134.2K

How much do analytics engineer remote dbt jobs pay per year?

As of Aug 9, 2026, the average yearly pay for analytics engineer remote dbt in Jenison, MI is $87,641.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,500.00 and $99,400.00 per year, depending on experience, location, and employer.

How does an analytics engineer working remotely with dbt typically collaborate with data analysts and other stakeholders?

Remote Analytics Engineers utilizing dbt often collaborate closely with data analysts, data scientists, and business stakeholders through virtual meetings, shared documentation, and version-controlled code repositories. They translate business requirements into data models, ensure data quality, and maintain data transformation pipelines. Regular syncs and agile ceremonies, like sprint planning and retrospectives, help keep communication clear and priorities aligned, while tools like Slack, Jira, and GitHub streamline collaboration across distributed teams.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis by building robust and scalable data models, often using tools like dbt (data build tool). In a remote setting, they are responsible for transforming raw data into well-structured datasets that analysts and business users can trust, collaborating with teams via digital communication tools. Their work includes writing SQL code, maintaining data pipelines, documenting data models, and ensuring data quality and consistency. Using dbt, Analytics Engineers automate and manage data transformations, making it easier for organizations to analyze their data efficiently.

What are the key skills and qualifications needed to thrive as a remote analytics engineer specializing in dbt?

To excel as a Remote Analytics Engineer focusing on dbt, you need strong SQL skills, data modeling expertise, and a background in analytics or computer science. Proficiency in dbt (data build tool), cloud data warehouses like Snowflake or BigQuery, and experience with version control systems such as Git are typically required. Outstanding problem-solving, communication, and collaboration skills make candidates stand out in remote and cross-functional environments. These competencies ensure efficient data pipeline development, reliable analytics solutions, and effective teamwork, which are crucial for delivering high-quality insights remotely.

What is the difference between Analytics Engineer Remote Dbt vs Data Engineer?

AspectAnalytics Engineer Remote DbtData Engineer
CredentialsSQL, Python, cloud platforms, Dbt certificationsSQL, Python, cloud platforms, data architecture certifications
Work EnvironmentRemote, collaborative with data teams, focus on analytics and data modelingOn-site or remote, infrastructure and pipeline development, focus on data systems
Industry UsageTech, finance, e-commerce, marketingTech, finance, healthcare, telecom

Analytics Engineer Remote Dbt professionals focus on building and maintaining data models using tools like Dbt, primarily supporting analytics and business insights. Data Engineers develop and manage data pipelines and infrastructure, often working on larger data systems. While both roles require SQL and cloud experience, Analytics Engineers emphasize data modeling and analytics, whereas Data Engineers focus on data architecture and pipeline development.

What cities near Jenison, MI are hiring for Analytics Engineer Remote Dbt jobs? Cities near Jenison, MI with the most Analytics Engineer Remote Dbt job openings:
Analytics Engineer Remote Dbt jobs near you
Infographic showing various Analytics Engineer Remote Dbt job openings in Jenison, MI as of June 2026, with employment types broken down into 86% Full Time, 13% Part Time, and 1% Temporary. Highlights an 52% Physical, 3% Hybrid, and 45% Remote job distribution, with an average salary of $87,641 per year, or $42.1 per hour.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Grand Rapids, MI • Remote

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 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