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Data Modernization Jobs in Michigan (NOW HIRING)

HireITPeople

Data Warehouse Architect 3

Lansing, MI · On-site

This role supports both on-premises and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

Innosoul inc

Data Warehouse Architect

Lansing, MI · On-site

This role supports both on premise and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

Zenfreed LLC

Data Warehouse Architect

Lansing, MI · On-site

This role supports both on-premise and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

LRS

Data Architect

Auburn Hills, MI · On-site

$40 - $60/hr

This role offers the chance to apply your data architecture and modernization expertise in support of meaningful work for one of our client partners. Our client is looking for an experienced Data ...

Zenfreed, LLC

Data Warehouse Architect

Lansing, MI

$66 - $82/hr

This role supports both on-premise and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

KēSTA I.T.

Data Warehouse Architect 161004

Lansing, MI · Hybrid

$60 - $80/hr

We Are Seeking an experienced Data Warehouse Architect to design, develop, and maintain enterprise data integration and ETL solutions that support critical business operations and data modernization ...

FastTek

Data Warehouse Architect

Lansing, MI

This role supports both on-premise and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D)

Programmers.io

Senior Databricks Architect

Detroit, MI · On-site

$64 - $84.25/hr

Collaborate with business and technical stakeholders to drive data modernization strategy. * Establish development best practices, coding standards, CI/CD, and DevOps/DataOps patterns. * Provide ...

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Data Modernization information

What jobs pay $500,000 a year in the US?

In the field of data modernization, senior roles such as Chief Data Officer, Data Science Director, or Vice President of Data often have salaries reaching or exceeding $500,000 annually, especially in large organizations. These positions typically require extensive experience, advanced skills in data architecture, analytics, and leadership, and may include performance bonuses and stock options.

What is the difference between Data Modernization vs Data Analyst?

AspectData ModernizationData Analyst
Primary FocusUpgrading and transforming data systems and infrastructureAnalyzing data to generate insights and reports
Skills RequiredData architecture, cloud platforms, database managementStatistical analysis, data visualization, SQL
Work EnvironmentIT departments, data engineering teamsBusiness units, analytics teams
CertificationsCloud certifications, data management certificationsData analysis, visualization certifications

Data Modernization involves upgrading data systems and infrastructure to improve efficiency and scalability, often requiring technical expertise in data architecture and cloud platforms. In contrast, Data Analysts focus on interpreting data, creating reports, and providing insights to support business decisions. While both roles work with data, their core responsibilities and skill sets differ significantly.

What jobs make $1,000,000 a year?

In the field of data modernization, high-paying roles such as Chief Data Officer, Data Science Director, or Chief Technology Officer can earn over $1 million annually, especially in large organizations or tech companies. These positions typically require extensive experience, advanced skills in data management, leadership, and often involve overseeing large teams and strategic initiatives.

What is data modernization?

Data modernization is the process of updating and transforming legacy data systems and infrastructure to more current, scalable, and efficient technologies. It often involves migrating data to cloud platforms, implementing new data management tools, and adopting modern analytics and automation techniques to improve data accessibility and decision-making.

What are some common challenges faced by professionals working in Data Modernization projects?

Professionals in Data Modernization often encounter challenges such as integrating legacy systems with modern cloud-based solutions, ensuring data quality during migration, and managing data security and compliance. Additionally, they may need to collaborate closely with cross-functional teams to align business goals with technical requirements. Adaptability and strong communication skills are important, as priorities can shift rapidly in response to evolving business needs and technology updates.

What are the key skills and qualifications needed to thrive in Data Modernization, and why are they important?

To thrive in Data Modernization, you need strong expertise in data architecture, cloud platforms, and data migration, often supported by a degree in computer science or information systems. Familiarity with tools like Azure, AWS, Snowflake, ETL frameworks, and certifications such as AWS Certified Data Analytics or Microsoft Azure Data Engineer are commonly required. Excellent problem-solving, project management, and communication skills help professionals effectively lead transformation initiatives and collaborate with stakeholders. These skills are crucial for ensuring seamless migration, maximizing data value, and driving innovation within organizations.

Which 3 jobs will survive AI?

Data modernization professionals, data analysts, and database administrators are likely to continue thriving as AI automates routine tasks but still requires human oversight, interpretation, and strategic decision-making. These roles involve managing complex data systems, ensuring data quality, and applying domain expertise that AI cannot fully replicate. Skills in data governance, programming, and understanding AI tools will enhance job security in this field.
What are popular job titles related to Data Modernization jobs in Michigan? For Data Modernization jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Modernization jobs in Michigan look for? The top searched job categories for Data Modernization jobs in Michigan are:
Data Modernization jobs near you
Infographic showing various Data Modernization job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Warehouse Architect 3

HireITPeople

Lansing, MI • On-site

Contractor

Posted 5 days ago

Job description

The ETL Developer is responsible for designing, developing, and maintaining high-quality data integration solutions using IBM DataStage and related technologies.

This role supports both on-premises and cloud environments, contributes to enterprise data modernization efforts, and plays a key role in migrating DataStage workloads to IBM Cloud Pak for Data (CP4D). The developer will collaborate with technical and business teams to deliver reliable, scalable, and secure data pipelines aligned with organizational objectives.

Responsibilities and Technical Skills:

• Develop, enhance, and optimize ETL pipelines using IBM DataStage, including parallel and server jobs, job sequencing, and performance tuning.

• Support the migration of on-premises DataStage jobs to IBM Cloud Pak for Data (CP4D), including code refactoring, testing, validation, and workflow

modernization.

• Use Python and XML to automate processes, perform data transformations, and integrate automation into ETL workflows.

• Work extensively in Linux/Unix environments to write shell scripts, manage file systems, monitor processes, and troubleshoot runtime issues.

• Apply Master Data Management (MDM) principles to ensure data quality, governance, and consistency across enterprise systems.

• Develop complex SQL queries for data extraction, transformation, validation, and performance improvement across relational database platforms.

• Work within Agile teams to support sprint activities, deployments, documentation, and continuous improvement practices.

• Collaborate with data architects, analysts, DBAs, and business users to ensure successful and accurate delivery of data solutions.

• Troubleshoot ETL issues, perform root-cause analysis, recommend improvements, and ensure adherence to data standards and security policies.

Top Skills & Years of Experience:

- 5+ years of experience with ETL (IBM DataStage) - Required

- 1+ years of exposure to Cloud Pak for data - Required

- 5+ years of experience with Unix/Linux

- 3+ years of experience with Master Data Management

Desired Skills:

- Previous Government experience.