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Senior Cloud Data Engineer Jobs in Michigan (NOW HIRING)

Senior AI Data Engineer

Grand Rapids, MI · On-site

$121K - $151K/yr

This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern ...

This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern ...

Senior Cloud Database Engineer

Dearborn, MI

$97K - $132K/yr

Senior Cloud Database Engineer #1059226 * We are seeking a Senior Cloud Database Engineer with 5+ ... Data-as-a-Product: Promote well-documented, discoverable, and consumable datasets. * Security ...

Seeking an experienced Data Engineer to design, build, and maintain our data infrastructure on Google Cloud Platform (GCP). The ideal candidate will possess a strong understanding of data ...

Senior Cloud Engineer

Troy, MI · On-site

$52.75 - $70.50/hr

SENIOR CLOUD ENGINEER Versigent designs and delivers the systems that move power through modern technology. From vehicles to robotics to energy platforms, our electrical distribution systems enable ...

Senior Cloud Engineer

Troy, MI · On-site

$53 - $70.75/hr

SENIOR CLOUD ENGINEER Versigent designs and delivers the systems that move power through modern technology. From vehicles to robotics to energy platforms, our electrical distribution systems enable ...

Senior Cloud Engineer

Troy, MI · On-site

$52.75 - $70.50/hr

SENIOR CLOUD ENGINEER Versigent designs and delivers the systems that move power through modern technology. From vehicles to robotics to energy platforms, our electrical distribution systems enable ...

Data Engineer

Okemos, MI · On-site

$103K - $124K/yr

Data Engineer Location: Okemos, MI (Hybrid/ Onsite) Duration: Long term Rate: Market F2F is must ... PL/SQL, Python, T-SQL, StreamSets, Snowflake Cloud Data Platform, and Informatica PowerCenter ...

$104K - $125K/yr

... cloud platforms, distributed processing, manufacturing data, AI/ML, and intelligent automation. - The opportunity to mentor Data Engineers and Senior Data Engineers and help build the next generation ...

Senior Data Engineer

Detroit, MI · On-site

$104K - $142K/yr

As a Senior Data Engineer, you'll design, develop, and maintain data platforms, mentor team members ... cloud data platforms • Develop relational and non-relational data models to meet user and ...

Data Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Ford Motor Company is seeking a Senior Technical Engineer to serve as a subject matter expert for ... Cloud data tools (GCP, BigQuery, etc.) * Automotive or industrial manufacturing experience

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

The Senior Data Scientist role resides within the Ford's Electric Vehicle organization. In this ... Lead the integration of new cloud technologies and AI tools (e.g., Vertex AI) into our workflows ...

Data Engineer

Okemos, MI · On-site

$103K - $124K/yr

DATA ENGINEER LOCATION: HYBRID IN OKEMOS, MI OFFICE 2 DAYS A WEEK + 3 DAYS REMOTE (ONLY LOCALS ... PL/SQL, Python, T-SQL, StreamSets, Snowflake Cloud Data Platform, and Informatica PowerCenter ...

Sr. Data Engineer

Grand Rapids, MI · On-site

$110K - $132K/yr

... cloud technologies-to empower smarter, faster decision-making across the business. This person will ... The Sr. Data Engineer must be a strong problem solver and multitasker who thrives managing multiple ...

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Showing results 1-20

Senior Cloud Data Engineer information

What is a senior cloud data engineer?

Senior Cloud Data Engineers are experienced professionals who design, build, and maintain data processing systems on cloud platforms. They are responsible for creating scalable, secure, and efficient data pipelines and ensuring data is accessible for analysis and reporting. These engineers often work with tools and services from cloud providers like AWS, Azure, or Google Cloud, and collaborate closely with data scientists, architects, and other stakeholders. Their expertise in both cloud infrastructure and data engineering allows organizations to leverage large volumes of data for business insights.

What are some common challenges faced by senior cloud data engineers when migrating on-premises data systems to the cloud?

Senior Cloud Data Engineers often encounter challenges such as ensuring data integrity and security during migration, minimizing downtime, and handling compatibility issues between legacy systems and cloud platforms. They also need to optimize data pipelines for scalability and cost-effectiveness in the new environment. Close collaboration with stakeholders from IT, security, and business units is crucial to align migration goals and manage expectations throughout the process.

What are the key skills and qualifications needed to thrive as a senior cloud data engineer, and why are they important?

To thrive as a Senior Cloud Data Engineer, you need advanced expertise in data engineering, cloud platforms (such as AWS, Azure, or Google Cloud), programming languages (like Python or Scala), and a strong foundation in database technologies. Proficiency with cloud-based tools (e.g., AWS Glue, Azure Data Factory), big data frameworks (such as Spark or Hadoop), and relevant certifications (like AWS Certified Data Analytics) is highly valued. Strong problem-solving skills, effective communication, and the ability to collaborate across teams help you excel in designing and optimizing complex data solutions. These skills ensure scalable, secure, and efficient data pipelines that support business analytics and innovation.

What is the difference between Senior Cloud Data Engineer vs Cloud Data Engineer?

AspectSenior Cloud Data EngineerCloud Data Engineer
Required CredentialsTypically requires 5+ years experience, advanced certifications (e.g., AWS Certified Data Analytics), and expertise in cloud platformsEntry to mid-level experience, foundational certifications, and basic cloud platform knowledge
Work EnvironmentDesigns and oversees complex data pipelines, mentors junior staff, and handles high-level architectureBuilds and maintains data pipelines, performs data integration, and supports data operations
Employer & Industry UsageUsed in large enterprises, tech companies, and data-driven organizationsCommon in startups, mid-sized companies, and organizations adopting cloud data solutions

The main difference between a Senior Cloud Data Engineer and a Cloud Data Engineer lies in experience, responsibilities, and expertise. Senior roles involve leadership, complex architecture, and mentorship, while Cloud Data Engineers focus on building and maintaining data pipelines. Both roles are essential in cloud data environments, but senior positions require more advanced skills and strategic oversight.

What are the most commonly searched types of Cloud Data Engineer jobs in Michigan?

The most popular types of Cloud Data Engineer jobs in Michigan are:

What job categories do people searching Senior Cloud Data Engineer jobs in Michigan look for?

The top searched job categories for Senior Cloud Data Engineer jobs in Michigan are:

What cities in Michigan are hiring for Senior Cloud Data Engineer jobs?

Cities in Michigan with the most Senior Cloud Data Engineer job openings:

Infographic showing various Senior Cloud Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior AI Data Engineer

Kiongroup

Grand Rapids, MI • On-site

$121K - $151K/yr

Full-time

Re-posted 28 days ago


Job description

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and interact with enterprise data and platform capabilities.
This role focuses on building the foundations that enable AI agents and intelligent applications to effectively leverage enterprise data, including context engineering, semantic understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform capabilities.
This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern software development practices. The ideal candidate combines strong technical execution skills with architectural thinking and the ability to design and deliver scalable AI capabilities that integrate seamlessly with enterprise data platforms and business workflows.We offer:
  • Career Development
  • Competitive Compensation and Benefits
  • Pay Transparency
  • Global Opportunities

Learn More Here:https://www.dematic.com/en-us/about/careers/what-we-offer

Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

The base pay range for this role is estimated to be $121,200.00 - $151,500.00 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge and skills.

Tasks and Qualifications:

This is What You Will do in This Role:

  • Evolve the Enterprise Data Platform into an AI-native platform by enabling intelligent discovery, understanding, and utilization of enterprise data.
  • Design and implement AI-driven capabilities and agents that enhance data platform capabilities, automate complex workflows, and improve how data is discovered, managed, governed, and consumed.
  • Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data.
  • Design architectures that enable AI systems to reason over enterprise data and safely interact with platform capabilities, APIs, services, and enterprise applications.
  • Develop scalable AI-enabled solutions that integrate with cloud data platforms, distributed systems, and modern software architectures.
  • Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence.
  • Apply strong data engineering and software engineering principles to build scalable, maintainable AI-enabled platform capabilities.
  • Partner with data, AI/ML, architecture, and product teams to identify and deliver high-impact AI capabilities for the enterprise data platform.
  • Mentor engineers and define best practices for AI-enabled data platform development.

What We are Looking For:

  • 8-12+ years of experience in enterprise software engineering, cloud data engineering, distributed systems, or data platform development.
  • Hands-on experience designing and building production AI systems, AI agents, or agentic workflows integrated with enterprise applications, APIs, and platform services.
  • Strong understanding of AI agent architectures, including tool calling, orchestration, context management, memory, evaluation, observability, and production deployment patterns.
  • Experience building AI-ready data platforms with capabilities such as semantic understanding, metadata intelligence, context engineering, and trusted data access.
  • Strong cloud data engineering experience, preferably in GCP, including BigQuery, Pub/Sub, Dataflow/Cloud Run, Composer/Airflow, and modern data platform services.
  • Strong programming skills in Python and experience building scalable software services, APIs, and microservice architectures.
  • Deep understanding of data engineering fundamentals, including data modeling, data contracts, metadata, lineage, governance, data quality, and batch/streaming architectures.
  • Experience integrating AI capabilities with enterprise data platforms and distributed systems.
  • Experience with modern data and cloud-native technologies such as Iceberg, Trino, Kubernetes, and Docker.
  • Experience designing secure, governed, and observable production AI solutions, including evaluation, monitoring, and operational excellence.

What Will Set You Apart:

  • Experience building AI agents that execute real-world enterprise workflows, beyond conversational assistants or prototypes.
  • Experience with AI frameworks and platforms such as Google ADK, Vertex AI, MCP, LangGraph, or similar technologies.
  • Experience applying RAG, embeddings, vector search, semantic layers, or knowledge graphs to enterprise AI solutions.
  • Experience with Data Mesh, domain-driven data architecture, or federated data platforms.
  • Supply chain, logistics, warehouse automation, or industrial domain experience.

Location & Authorization:This is a hybrid role requiring proximity to one of our U.S. offices (Atlanta GA, Grand Rapids MI, Milwaukee WI).Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.

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