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Aws Data Engineer Jobs in Michigan (NOW HIRING)

Senior Forward Deployed Engineer- AWS

Detroit, MI · On-site

$103K - $142K/yr

Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

Lead Forward Deployed Engineer - AWS

Detroit, MI · On-site

$101K - $133K/yr

Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ... Solution Engineering * Build AI-enabled solutions, agentic platforms, and workflows across ...

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Stefanini is looking for a Google Cloud Platform Data Engineer, Dearborn, MI For quick apply ... AWS Glue, S3, Redshift, and Athena, Azure Data Factory and Databricks, Google BigQuery and ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $136K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $137K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $136K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $137K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $137K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Troy, MI · Hybrid

$100K - $137K/yr

Required Experience (Must Have) Expert Python & SQL Developer Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) Strong Experience with Semi-Structured Data (XML ...

Senior Data Engineer

Detroit, MI · On-site

$104K - $142K/yr

... including AWS Lambda functions • Proficiency in a functional or object-oriented programming ... data systems • Experience mentoring and developing other engineers Company : Own the Dream.

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) * Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet) * Strong Automation Experience

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) * Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet) * Strong Automation Experience

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) * Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet) * Strong Automation Experience

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) * Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet) * Strong Automation Experience

Strong AWS Experience (Lambda, Glue, State Machines, Fargate, Cloud Formation, RedShift) * Strong Experience with Semi-Structured Data (XML, CSV, JSON, Parquet) * Strong Automation Experience

Showing results 41-60

Aws Data Engineer information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do aws data engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for aws data engineer in Michigan is $113,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $119,800.00 per year, depending on experience, location, and employer.

What is an AWS data engineer?

AWS Data Engineers are professionals who design, build, and maintain data pipelines and architectures on Amazon Web Services (AWS). They work with large datasets, using AWS services such as Amazon S3, Redshift, Glue, and EMR to collect, transform, and store data for analytics or business intelligence. Their responsibilities often include ensuring data reliability, scalability, and security while optimizing data workflows and integrating various cloud-based tools. AWS Data Engineers collaborate with data scientists, analysts, and other stakeholders to enable data-driven decision-making. They typically have strong skills in programming, cloud infrastructure, and database management.

What are the key skills and qualifications needed to thrive as an AWS data engineer?

To thrive as an AWS Data Engineer, you need strong skills in data modeling, ETL processes, SQL, and a solid understanding of AWS services, typically supported by a degree in computer science or a related field. Familiarity with AWS tools like Redshift, Glue, S3, Lambda, and certifications such as AWS Certified Data Analytics are highly beneficial. Problem-solving abilities, effective communication, and adaptability are crucial soft skills for collaborating with teams and managing complex data projects. Mastery of these skills ensures efficient data pipeline development, reliable data solutions, and the ability to support business intelligence in a cloud environment.

What are some common challenges AWS data engineers face when managing large-scale data pipelines?

AWS Data Engineers often encounter challenges related to optimizing data pipelines for scalability and cost efficiency. Managing data ingestion from diverse sources, ensuring data quality, and handling real-time data processing can be complex at scale. Additionally, they must regularly monitor and troubleshoot pipeline failures, integrate new AWS services, and collaborate closely with data scientists, analysts, and DevOps teams to ensure data accessibility and security. Proactively addressing these challenges is vital for maintaining reliable and efficient data workflows.

What is the difference between Aws Data Engineer vs Data Analyst?

AspectAws Data EngineerData Analyst
Required CredentialsAWS certifications, SQL, Python, data engineering skillsSQL, Excel, data visualization tools, sometimes basic programming
Work EnvironmentCloud platforms, big data environments, data pipelinesBusiness intelligence tools, spreadsheets, reporting dashboards
Employer & Industry UsageTech companies, cloud service providers, enterprises using AWSMarketing, finance, healthcare, and other industries analyzing data

While both roles work with data, Aws Data Engineers focus on building and maintaining data pipelines in cloud environments using AWS tools, whereas Data Analysts interpret data to generate insights and reports. The roles often complement each other in data-driven organizations.

Is AWS Data Engineer in demand?

AWS Data Engineers are in high demand due to the increasing adoption of cloud data platforms and the need for scalable data processing solutions. Skills in AWS services like S3, Redshift, and Glue, along with data modeling and ETL expertise, are highly sought after by employers across various industries.

What does an AWS Data Engineer do?

An AWS Data Engineer designs, builds, and maintains data pipelines and infrastructure on Amazon Web Services. They work with tools like AWS Glue, Redshift, S3, and Lambda to process and analyze large datasets, ensuring data quality and security. Strong programming skills and knowledge of cloud architecture are essential for this role.

What is the salary of AWS Data Engineer?

The average salary for an AWS Data Engineer typically ranges from $90,000 to $150,000 annually, depending on experience, location, and certifications such as AWS Certified Data Analytics. Senior roles or those with specialized skills in cloud architecture may earn higher salaries.

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

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

Infographic showing various Aws Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $113,060 per year, or $54.4 per hour.

Senior Forward Deployed Engineer- AWS

Deloitte

Detroit, MI • On-site

$103K - $142K/yr

Full-time

Re-posted 24 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

46th of 152 rated financial services


Job description

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Qualifications:

At Deloitte, Forward Deployed Engineers (FDE) don't just build AI solutions, they help clients turn AI ambition into enterprise-scale impact, pairing leading class engineering with pod-based delivery and vertical expertise. If you thrive at the intersection of product, engineering, problem-solving, and client impact, this role puts you at the forefront of AI transformations.

Work you'll do

As an AWS AI&Data FDE, you will work side by side with senior functional and technical client team members to rapidly prototype and deliver high-impact GenAI-enabled solutions. This requires a highly motivated practitioner who moves with speed and precision, building working software, engaging confidently with senior stakeholders and engineers to bring measurable business impact from day one. Additional responsibilities include:

Client Engagement

  • Embed with clients to identify business needs and translate high-value GenAI use cases into solutions.
  • Partner with leaders, product owners, architects, and engineers to align priorities and delivery.
  • Lead working sessions to shape solutions and drive client outcomes.
  • Prototype and deliver working AI solutions using industry expertise and emerging capabilities.
  • Contribute independently within an FDE pod while mentoring newer team members.

Solution Engineering

  • Build AI-enabled solutions, agentic platforms, and workflows across enterprise AI platforms.
  • Develop scalable AI engineering patterns, tool-use approaches, and human-in-the-loop controls.
  • Apply architecture decisions that balance quality, safety, latency, cost, and model risk.
  • Deliver production-quality code using strong practices in testing, CI/CD, logging, versioning, and documentation.
  • Design extensible functionality, support sprint sizing, and align solutions with senior team members.
  • Contribute reusable assets including code, prompt libraries, runbooks, and reference implementations.


The team

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.

Required qualifications 

  • Bachelor's degree (or equivalent) in Computer Science, Data Science or Engineering.
  • 5+ years of experience in software engineering, data engineering, data science, or analytics engineering. 
  • 1+ years of hands-on experience building and deploying GenAI/LLM-powered solutions in client or production environments
  • 1+ years of experience with AWS AI&Data including hands on experience with one of the following key platforms/products: Amazon Bedrock, Bedrock AgentCore, Strands Agents SDK, Knowledge Bases, Guardrails
  • 1+ years of experience with AWS Neptune and OpenSearch
  • 1+ years of experience leading project workstreams/engagements and translating business problems into AI solutions
  • At least 3 of 6 certifications from the following list: AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate)
  • 1+ years of experience building reliable, maintainable, and well-documented code 
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred qualifications

  • Experience with cloud environments (AWS, Azure, and/or Google Cloud) and common platform services (storage, compute, IAM, networking)
  • Demonstrated ability to work directly alongside client technical teams and program stakeholders in fast-paced, ambiguous delivery environments 
  • Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation
  • Experience with MLOps/LLMOps practices: evaluation frameworks, model monitoring, and prompt management 
  • Experience with SageMaker fine-tuning (SFT and RFT) for domain SLMs
  • Experience integrating LLM solutions with enterprise systems via APIs, microservices, or event-driven architectures 
  • Experience operating within hybrid onshore/offshore teams 
  • Familiarity with security, privacy, and compliance considerations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


Education:Bachelor's DegreeEmployment Type:

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