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Remote Azure Data Factory Jobs in Michigan (NOW HIRING)

Gordon Food Service

Intermediate Data Engineer

Wyoming, MI · On-site +1

$103K - $124K/yr

Hybrid schedule, 4 days in office in Wyoming, MI or Atlanta, GA with 1 day remote What you'll bring ... GCP, AWS, Azure) preferred. * Preferred tool experience include but not limited to Apache Airflow ...

Utilidata

Principal Data Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

Strong experience with cloud data infrastructure (AWS, GCP, or Azure) and the surrounding ecosystem * Demonstrated ability to lead technical teams, set direction, and grow engineers without relying ...

Kobie Marketing

Sr. Data Engineer

Detroit, MI · Remote

$104K - $142K/yr

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... Cloud experience with Azure and/or AWS. * Comfort working independently across concurrent projects ...

2Bridge Partners

Staff Software Engineer

Detroit, MI · On-site +1

$170K - $200K/yr

Design, develop, and maintain complex software systems using C#, .NET, Azure, AWS, or another cloud ... Open to remote or hybrid if in the Detroit metro or Ann Arbor area.

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All JobsRemote Azure Data Factory JobsRemote Azure Data Factory Jobs in Michigan

Remote Azure Data Factory information

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 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 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 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 popular job titles related to Remote Azure Data Factory jobs in Michigan? For Remote Azure Data Factory jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Azure Data Factory jobs in Michigan look for? The top searched job categories for Remote Azure Data Factory jobs in Michigan are:
What cities in Michigan are hiring for Remote Azure Data Factory jobs? Cities in Michigan with the most Remote Azure Data Factory job openings:
Remote Azure Data Factory jobs near you
Infographic showing various Remote Azure Data Factory job openings in Michigan as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.
Principal Data Scientist (Remote)

Principal Data Scientist (Remote)

Emergent Holdings

Lansing, MI • On-site, Remote

Full-time

Posted 3 days ago

Job description

Job Description
SUMMARY
AF Group is seeking a Principal Data Scientist with expertise in either Commercial Property or Personal Homeowners insurance to serve as an individual contributor and technical authority on applying advanced analytics and machine learning to complex business problems, including pricing, risk selection, and other underwriting challenges. This role owns the end-to-end analytical lifecycle, from problem formulation and model development through deployment, monitoring, and governance. Partners closely with Actuarial, MLOps, and IT to deliver scalable, production-ready solutions. The Principal Data Scientist ensures long-term model performance through rigorous validation, drift monitoring, and audit-ready documentation, while advancing analytical best practices and evaluating emerging techniques relevant to commercial P&C insurance.
RESPONSIBILITIES/TASKS:
  • Acquires, organizes, and cleanses structured and unstructured data.
  • Conducts in-depth analysis to uncover trends, risks, and business opportunities.
  • Applies statistical modeling, machine learning, and advanced analytics to develop predictive and prescriptive solutions.
  • Evaluate solution performance using statistically rigorous methods and measure the impact to business outcomes.
  • Collaborate with MLOps and IT partners to transition solution prototypes from pilot validation into production environments.
  • Ensures ongoing model health through post-deployment monitoring, drift detection, and audit-compliant governance practices.
  • Creates and communicates results to senior level audiences of varying backgrounds, using business-facing presentations, reports, and dashboards.
  • Author and maintain comprehensive technical documentation for data lineage, codebases, results, and production changes.
  • Provides technical and project guidance, including peer review of work, for data science team.
  • Leads the evaluation of new analytic tools and processes.
  • Drives investigation and adoption of advanced machine learning and AI innovations.

EDUCATION:
Bachelor's Degree in Data Science, Statistics, Mathematics, Operations Research, Actuarial Science, Computer Science, Engineering, Physics or related technical field required. Advanced degree preferred.
EXPERIENCE:
10 years of experience in data science or related advanced analytics domains, including research and teaching, with 3+ years of technical leadership.
REQUIRED SKILLS/KNOWLEDGE/ABILITIES
  • 3+ years of experience supporting underwriting functions, including loss modeling, for Commercial Property (preferred) or Personal Homeowners insurance.
  • Demonstrated expertise using Poisson, Gamma, and Tweedie distributions to build loss ratio, pure premium, and frequency-severity loss models for pricing.
  • Extensive experience leveraging supervised learning models (e.g., XGBoost, GLM, etc.) and unsupervised techniques (e.g., K-means, PCA, etc.) to solve complex data science problems.
  • Advanced Python programming skills supporting data science, including scikit-learn and pandas.
  • Proficient data wrangling and ETL abilities using SQL on relational databases.
  • Comfortable explaining machine learning models with partial dependence plots and SHAP values.
  • Ability to conduct experiments e.g., A/B Testing, to evaluate the causal impact of model-driven decisions.
  • Experience using version control tools such as Git and Azure DevOps.
  • Experience working in cloud computing environments such as Azure, AWS, GCP, etc.

PREFERRED SKILLS/KNOWLEDGE/ABILITIES
  • Experience supporting at least one other commercial or personal line outside of Property lines.
  • In-depth understanding of General Liability (aka Casualty), Workers Compensation, or Commercial Vehicle insurance.
  • Knowledge of actuarial concepts and terminology used in pricing and ratemaking.
  • Experience with Claims, Marketing, or Operations functions within P&C insurance settings.
  • Ability to develop Agentic AI solutions to drive autonomous decision-making and task orchestration.
  • Familiarity with causal modeling techniques such as Meta-learners, Causal Forest, Double ML, etc.
  • Knowledge of advanced neural net architectures like LSTM, CNN, Transformers, Graph NN, etc.
  • Understanding of NLP concepts such as topic modeling, Word2Vec, sentiment analysis, OCR, etc.
  • Experience programming in the R language.
  • Ability to build interactive dashboards using frameworks such as Plotly Dash, Power BI, Flask, etc.

ADDITIONAL INFORMATION:
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. This job description does not constitute a contract for employment.
PAY RANGE:
"Actual compensation decision relies on the consideration of internal equity, candidate's skills and professional experience, geographic location, market and other potential factors. It is not standard practice for an offer to be at or near the top of the range, and therefore a reasonable estimate for this role is between $137,900 and $231,000."
We are an Equal Opportunity Employer. We will not tolerate discrimination or harassment in any form. Candidates for the position stated above are hired on an "at will" basis. Nothing herein is intended to create a contract.
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